SG10201709943RA - A convolutional neural network (cnn) system based on resolution-limited small-scale cnn modules - Google Patents
A convolutional neural network (cnn) system based on resolution-limited small-scale cnn modulesInfo
- Publication number
- SG10201709943RA SG10201709943RA SG10201709943RA SG10201709943RA SG10201709943RA SG 10201709943R A SG10201709943R A SG 10201709943RA SG 10201709943R A SG10201709943R A SG 10201709943RA SG 10201709943R A SG10201709943R A SG 10201709943RA SG 10201709943R A SG10201709943R A SG 10201709943RA
- Authority
- SG
- Singapore
- Prior art keywords
- cnn
- resolution
- system based
- scale
- input image
- Prior art date
Links
- 238000013527 convolutional neural network Methods 0.000 title abstract 9
- 238000000034 method Methods 0.000 abstract 1
- 230000007935 neutral effect Effects 0.000 abstract 1
- 238000005192 partition Methods 0.000 abstract 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24133—Distances to prototypes
- G06F18/24143—Distances to neighbourhood prototypes, e.g. restricted Coulomb energy networks [RCEN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/50—Image enhancement or restoration using two or more images, e.g. averaging or subtraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/246—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments
- G06T7/248—Analysis of motion using feature-based methods, e.g. the tracking of corners or segments involving reference images or patches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
- G06V10/443—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components by matching or filtering
- G06V10/449—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters
- G06V10/451—Biologically inspired filters, e.g. difference of Gaussians [DoG] or Gabor filters with interaction between the filter responses, e.g. cortical complex cells
- G06V10/454—Integrating the filters into a hierarchical structure, e.g. convolutional neural networks [CNN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/19—Recognition using electronic means
- G06V30/191—Design or setup of recognition systems or techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
- G06V30/19173—Classification techniques
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/169—Holistic features and representations, i.e. based on the facial image taken as a whole
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/25—Fusion techniques
- G06F18/251—Fusion techniques of input or preprocessed data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/28—Indexing scheme for image data processing or generation, in general involving image processing hardware
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20021—Dividing image into blocks, subimages or windows
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20084—Artificial neural networks [ANN]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20221—Image fusion; Image merging
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20212—Image combination
- G06T2207/20224—Image subtraction
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
- G06T2207/30201—Face
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2210/00—Indexing scheme for image generation or computer graphics
- G06T2210/12—Bounding box
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/62—Text, e.g. of license plates, overlay texts or captions on TV images
- G06V20/625—License plates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
- G06V30/10—Character recognition
- G06V30/32—Digital ink
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/178—Human faces, e.g. facial parts, sketches or expressions estimating age from face image; using age information for improving recognition
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Mathematical Physics (AREA)
- Computational Linguistics (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Human Computer Interaction (AREA)
- Neurology (AREA)
- Databases & Information Systems (AREA)
- Medical Informatics (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Biodiversity & Conservation Biology (AREA)
- Image Analysis (AREA)
Abstract
A CONVOLUTIONAL NEURAL NETWORK (CNN) SYSTEM BASED ON RESOLUTION-LIMITED SMALL-SCALE CNN MODULES Embodiments of a convolutional neutral network (CNN) system based on using resolution-limited small-scale CNN modules are disclosed. In some embodiments, a CNN system includes: a receiving module for receiving an input image of a first image size, the receiving module can be used to partition the input image into a set of subimages of a second image size; a first processing stage that includes a first hardware CNN module configured with a maximum input image size, the first hardware CNN module is configured to sequentially receive the set of subimages and sequentially process the received subimages to generate a set of outputs; a merging module for merging the sets of outputs into a set of merged feature maps; and a second processing stage for receiving the set of feature maps and processing the set of feature maps to generate an output including at least one prediction on the input image. FIG. B 40
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US201662428497P | 2016-11-30 | 2016-11-30 | |
US15/441,194 US10360494B2 (en) | 2016-11-30 | 2017-02-23 | Convolutional neural network (CNN) system based on resolution-limited small-scale CNN modules |
Publications (1)
Publication Number | Publication Date |
---|---|
SG10201709943RA true SG10201709943RA (en) | 2018-06-28 |
Family
ID=62190214
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG10201709945UA SG10201709945UA (en) | 2016-11-30 | 2017-11-30 | Face detection using small-scale convolutional neural network (cnn) modules for embedded systems |
SG10201709943RA SG10201709943RA (en) | 2016-11-30 | 2017-11-30 | A convolutional neural network (cnn) system based on resolution-limited small-scale cnn modules |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
SG10201709945UA SG10201709945UA (en) | 2016-11-30 | 2017-11-30 | Face detection using small-scale convolutional neural network (cnn) modules for embedded systems |
Country Status (4)
Country | Link |
---|---|
US (3) | US10360494B2 (en) |
KR (2) | KR20180062422A (en) |
CA (2) | CA2986860A1 (en) |
SG (2) | SG10201709945UA (en) |
Families Citing this family (147)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10559091B2 (en) * | 2015-09-11 | 2020-02-11 | Nec Corporation | Object counting device, object counting method, object counting program, and object counting system |
US10592729B2 (en) * | 2016-01-21 | 2020-03-17 | Samsung Electronics Co., Ltd. | Face detection method and apparatus |
CN106157307B (en) * | 2016-06-27 | 2018-09-11 | 浙江工商大学 | A kind of monocular image depth estimation method based on multiple dimensioned CNN and continuous CRF |
US10303977B2 (en) * | 2016-06-28 | 2019-05-28 | Conduent Business Services, Llc | System and method for expanding and training convolutional neural networks for large size input images |
US10366302B2 (en) * | 2016-10-10 | 2019-07-30 | Gyrfalcon Technology Inc. | Hierarchical category classification scheme using multiple sets of fully-connected networks with a CNN based integrated circuit as feature extractor |
US10360494B2 (en) * | 2016-11-30 | 2019-07-23 | Altumview Systems Inc. | Convolutional neural network (CNN) system based on resolution-limited small-scale CNN modules |
CN106778856A (en) * | 2016-12-08 | 2017-05-31 | 深圳大学 | A kind of object identification method and device |
US10318827B2 (en) * | 2016-12-19 | 2019-06-11 | Waymo Llc | Object detection neural networks |
US10546231B2 (en) * | 2017-01-23 | 2020-01-28 | Fotonation Limited | Method for synthesizing a neural network |
WO2018152741A1 (en) * | 2017-02-23 | 2018-08-30 | Nokia Technologies Oy | Collaborative activation for deep learning field |
CN106952269B (en) * | 2017-02-24 | 2019-09-20 | 北京航空航天大学 | The reversible video foreground object sequence detection dividing method of neighbour and system |
US10692502B2 (en) * | 2017-03-03 | 2020-06-23 | Pindrop Security, Inc. | Method and apparatus for detecting spoofing conditions |
CN106683680B (en) * | 2017-03-10 | 2022-03-25 | 百度在线网络技术(北京)有限公司 | Speaker recognition method and device, computer equipment and computer readable medium |
US10185895B1 (en) * | 2017-03-23 | 2019-01-22 | Gopro, Inc. | Systems and methods for classifying activities captured within images |
US10496895B2 (en) * | 2017-03-28 | 2019-12-03 | Facebook, Inc. | Generating refined object proposals using deep-learning models |
US10810371B2 (en) | 2017-04-06 | 2020-10-20 | AIBrain Corporation | Adaptive, interactive, and cognitive reasoner of an autonomous robotic system |
US11151992B2 (en) * | 2017-04-06 | 2021-10-19 | AIBrain Corporation | Context aware interactive robot |
US10963493B1 (en) | 2017-04-06 | 2021-03-30 | AIBrain Corporation | Interactive game with robot system |
US10929759B2 (en) | 2017-04-06 | 2021-02-23 | AIBrain Corporation | Intelligent robot software platform |
US10839017B2 (en) | 2017-04-06 | 2020-11-17 | AIBrain Corporation | Adaptive, interactive, and cognitive reasoner of an autonomous robotic system utilizing an advanced memory graph structure |
US10621725B2 (en) * | 2017-04-12 | 2020-04-14 | Here Global B.V. | Small object detection from a large image |
US10515199B2 (en) * | 2017-04-19 | 2019-12-24 | Qualcomm Incorporated | Systems and methods for facial authentication |
US11238559B2 (en) * | 2017-04-21 | 2022-02-01 | Semiconductor Energy Laboratory Co., Ltd. | Image processing method and image receiving apparatus |
US10410314B2 (en) * | 2017-04-27 | 2019-09-10 | Apple Inc. | Systems and methods for crossfading image data |
CN107124609A (en) * | 2017-04-27 | 2017-09-01 | 京东方科技集团股份有限公司 | A kind of processing system of video image, its processing method and display device |
US10552663B2 (en) * | 2017-05-02 | 2020-02-04 | Techcyte, Inc. | Machine learning classification and training for digital microscopy cytology images |
CN116629743A (en) | 2017-05-23 | 2023-08-22 | 沃尔玛阿波罗有限责任公司 | Automated inspection system |
US10282589B2 (en) * | 2017-08-29 | 2019-05-07 | Konica Minolta Laboratory U.S.A., Inc. | Method and system for detection and classification of cells using convolutional neural networks |
CN107491771A (en) * | 2017-09-21 | 2017-12-19 | 百度在线网络技术(北京)有限公司 | Method for detecting human face and device |
CN107644209A (en) * | 2017-09-21 | 2018-01-30 | 百度在线网络技术(北京)有限公司 | Method for detecting human face and device |
KR102468729B1 (en) * | 2017-09-29 | 2022-11-21 | 삼성전자주식회사 | Electronic device and object sensing method therof |
WO2019076467A1 (en) * | 2017-10-20 | 2019-04-25 | Toyota Motor Europe | Method and system for processing an image and determining viewpoints of objects |
CN107742107B (en) * | 2017-10-20 | 2019-03-01 | 北京达佳互联信息技术有限公司 | Facial image classification method, device and server |
CN108052862B (en) * | 2017-11-09 | 2019-12-06 | 北京达佳互联信息技术有限公司 | Age estimation method and device |
KR20200100672A (en) * | 2017-12-04 | 2020-08-26 | 옵티멈 세미컨덕터 테크놀로지스 인코포레이티드 | Neural network accelerator system and architecture |
US20190188729A1 (en) * | 2017-12-18 | 2019-06-20 | Beijing Jingdong Shangke Information Technology Co., Ltd. | System and method for detecting counterfeit product based on deep learning |
TWI649698B (en) * | 2017-12-21 | 2019-02-01 | 財團法人工業技術研究院 | Object detection device, object detection method, and computer readable medium |
US11551362B2 (en) * | 2018-01-10 | 2023-01-10 | Institut De Recherche Sur Les Cancers De I | Automatic segmentation process of a 3D medical image by several neural networks through structured convolution according to the geometry of the 3D medical image |
US11448632B2 (en) | 2018-03-19 | 2022-09-20 | Walmart Apollo, Llc | System and method for the determination of produce shelf life |
WO2019204700A1 (en) * | 2018-04-19 | 2019-10-24 | University Of South Florida | Neonatal pain identification from neonatal facial expressions |
IT201800003188A1 (en) * | 2018-05-25 | 2019-11-25 | Head counter device and digital image processing method | |
US11568629B2 (en) | 2018-06-06 | 2023-01-31 | Cognex Corporation | System and method for finding and classifying patterns in an image with a vision system |
CN110581970A (en) * | 2018-06-07 | 2019-12-17 | 北京华泰科捷信息技术股份有限公司 | network video storage device with face recognition and analysis function and method |
CA3105272A1 (en) * | 2018-06-29 | 2020-01-02 | Wrnch Inc. | Human pose analysis system and method |
KR101942219B1 (en) | 2018-07-05 | 2019-01-24 | 고재성 | Apparatus and method for waste image identification using convolution neural network |
KR102570562B1 (en) * | 2018-07-16 | 2023-08-24 | 삼성전자주식회사 | Image processing apparatus and operating method for the same |
KR102108391B1 (en) * | 2018-07-18 | 2020-05-12 | 주식회사 영국전자 | Moving Object Linkage Tracking System and Method Using Multiple Cameras |
CN109285157A (en) * | 2018-07-24 | 2019-01-29 | 深圳先进技术研究院 | Myocardium of left ventricle dividing method, device and computer readable storage medium |
WO2020023762A1 (en) | 2018-07-26 | 2020-01-30 | Walmart Apollo, Llc | System and method for produce detection and classification |
CN109272107A (en) * | 2018-08-10 | 2019-01-25 | 广东工业大学 | A method of improving the number of parameters of deep layer convolutional neural networks |
US10747989B2 (en) * | 2018-08-21 | 2020-08-18 | Software Ag | Systems and/or methods for accelerating facial feature vector matching with supervised machine learning |
KR101941994B1 (en) * | 2018-08-24 | 2019-01-24 | 전북대학교산학협력단 | System for pedestrian detection and attribute extraction based on a joint deep network |
US11579921B2 (en) * | 2018-08-29 | 2023-02-14 | Alibaba Group Holding Limited | Method and system for performing parallel computations to generate multiple output feature maps |
KR102553146B1 (en) | 2018-09-13 | 2023-07-07 | 삼성전자주식회사 | Image processing apparatus and operating method for the same |
JP6695947B2 (en) * | 2018-09-21 | 2020-05-20 | ソニーセミコンダクタソリューションズ株式会社 | Solid-state imaging system, image processing method and program |
US10733742B2 (en) | 2018-09-26 | 2020-08-04 | International Business Machines Corporation | Image labeling |
US11176427B2 (en) | 2018-09-26 | 2021-11-16 | International Business Machines Corporation | Overlapping CNN cache reuse in high resolution and streaming-based deep learning inference engines |
CN109271957B (en) * | 2018-09-30 | 2020-10-20 | 厦门市巨龙信息科技有限公司 | Face gender identification method and device |
DE102018216962A1 (en) * | 2018-10-02 | 2020-04-02 | Robert Bosch Gmbh | Process for high-resolution, scalable domain translation |
KR102108854B1 (en) * | 2018-10-05 | 2020-05-12 | 재단법인대구경북과학기술원 | Real-time object detection method and apparatus by deep learning network model |
IL282172B2 (en) | 2018-10-11 | 2024-02-01 | Tesla Inc | Systems and methods for training machine models with augmented data |
US11715059B2 (en) | 2018-10-12 | 2023-08-01 | Walmart Apollo, Llc | Systems and methods for condition compliance |
KR102127369B1 (en) * | 2018-10-17 | 2020-06-26 | 엔에이치엔 주식회사 | Neural network system for detecting Palmprint and method for providing Palmprint-based fortune forecasting service |
CN111079473A (en) * | 2018-10-19 | 2020-04-28 | 北京奇虎科技有限公司 | Gender identification method, gender identification device, electronic equipment and computer-readable storage medium |
KR102169543B1 (en) | 2018-11-08 | 2020-10-23 | 주식회사 소이넷 | Method for setting artificial intelligence execution model and system for acceleration a.i execution |
WO2020106332A1 (en) | 2018-11-20 | 2020-05-28 | Walmart Apollo, Llc | Systems and methods for assessing products |
KR20200066952A (en) | 2018-12-03 | 2020-06-11 | 삼성전자주식회사 | Method and apparatus for performing dilated convolution operation in neural network |
KR102092205B1 (en) * | 2018-12-03 | 2020-03-23 | 한국과학기술원 | Image processing method and apparatus for generating super resolution, inverse tone mapping and joint super resolution-inverse tone mapping processed multiple output image |
US10977548B2 (en) | 2018-12-05 | 2021-04-13 | Bank Of America Corporation | Generation of capsule neural networks for enhancing image processing platforms |
KR102055645B1 (en) * | 2018-12-07 | 2020-01-22 | 아주대학교산학협력단 | High speed convolution method for deep learning |
KR102096617B1 (en) * | 2018-12-12 | 2020-04-02 | 충남대학교산학협력단 | Driver drowsiness detection system using image and ppg data based on multimodal deep learning |
DE102018222202A1 (en) * | 2018-12-18 | 2020-06-18 | Volkswagen Aktiengesellschaft | Method and device for operating a machine learning model |
CN109726678B (en) * | 2018-12-28 | 2023-02-28 | 深圳市捷顺科技实业股份有限公司 | License plate recognition method and related device |
CN109711413B (en) * | 2018-12-30 | 2023-04-07 | 陕西师范大学 | Image semantic segmentation method based on deep learning |
CN109753931A (en) * | 2019-01-04 | 2019-05-14 | 广州广电卓识智能科技有限公司 | Convolutional neural networks training method, system and facial feature points detection method |
US11080835B2 (en) | 2019-01-09 | 2021-08-03 | Disney Enterprises, Inc. | Pixel error detection system |
CN109711384A (en) * | 2019-01-09 | 2019-05-03 | 江苏星云网格信息技术有限公司 | A kind of face identification method based on depth convolutional neural networks |
CN109726703B (en) * | 2019-01-11 | 2021-06-18 | 浙江工业大学 | Face image age identification method based on improved ensemble learning strategy |
US10402695B1 (en) * | 2019-01-23 | 2019-09-03 | StradVision, Inc. | Learning method and learning device for convolutional neural network using 1×H convolution for image recognition to be used for hardware optimization, and testing method and testing device using the same |
CN109840489A (en) * | 2019-01-24 | 2019-06-04 | 深圳市云恩科技有限公司 | A kind of ferry pedestrian movement tracing detection system and its detection method |
CN111488475A (en) * | 2019-01-29 | 2020-08-04 | 北京三星通信技术研究有限公司 | Image retrieval method, image retrieval device, electronic equipment and computer-readable storage medium |
US10915809B2 (en) | 2019-02-04 | 2021-02-09 | Bank Of America Corporation | Neural network image recognition with watermark protection |
CN109886241A (en) * | 2019-03-05 | 2019-06-14 | 天津工业大学 | Driver fatigue detection based on shot and long term memory network |
CN109934149B (en) * | 2019-03-06 | 2022-08-09 | 百度在线网络技术(北京)有限公司 | Method and apparatus for outputting information |
US10872258B2 (en) | 2019-03-15 | 2020-12-22 | Huawei Technologies Co., Ltd. | Adaptive image cropping for face recognition |
US11222069B2 (en) * | 2019-03-31 | 2022-01-11 | Cortica Ltd. | Low-power calculation of a signature of a media unit |
KR102083166B1 (en) * | 2019-04-22 | 2020-03-02 | 한국과학기술원 | Image processing method and apparatus |
CN110046595B (en) * | 2019-04-23 | 2022-08-09 | 福州大学 | Cascade multi-scale based dense face detection method |
CN110022466A (en) * | 2019-04-24 | 2019-07-16 | 中科院成都信息技术股份有限公司 | A kind of video analysis platform and its control method based on wisdom big data |
CN111027366B (en) * | 2019-04-30 | 2020-11-27 | 六安木子可科技有限公司 | Adaptive facial signal processing platform |
CN110222566A (en) * | 2019-04-30 | 2019-09-10 | 北京迈格威科技有限公司 | A kind of acquisition methods of face characteristic, device, terminal and storage medium |
CN110334577B (en) * | 2019-05-05 | 2022-09-16 | 四川盛通智联网络科技有限公司 | Face recognition method based on Haisi security chip |
CN110135313A (en) * | 2019-05-07 | 2019-08-16 | 西安募格网络科技有限公司 | A kind of Age estimation method based on convolutional neural networks |
CN110097021B (en) * | 2019-05-10 | 2022-09-06 | 电子科技大学 | MTCNN-based face pose estimation method |
KR102420104B1 (en) * | 2019-05-16 | 2022-07-12 | 삼성전자주식회사 | Image processing apparatus and operating method for the same |
US10831417B1 (en) * | 2019-06-17 | 2020-11-10 | Kyocera Document Solutions Inc. | Convolutional neural network based copy or print wizard |
CN112115740B (en) * | 2019-06-19 | 2024-04-09 | 京东科技信息技术有限公司 | Method and apparatus for processing image |
CN112149449A (en) * | 2019-06-26 | 2020-12-29 | 北京华捷艾米科技有限公司 | Face attribute recognition method and system based on deep learning |
US10748650B1 (en) * | 2019-07-17 | 2020-08-18 | Richard Ricci | Machine learning of dental images for E-commerce |
CN110351526A (en) * | 2019-07-23 | 2019-10-18 | 北京中安信合科技有限公司 | A kind of personnel's supervisory systems based on artificial intelligence technology |
US11113822B2 (en) * | 2019-08-14 | 2021-09-07 | International Business Machines Corporation | Moving object identification from a video stream |
KR102641117B1 (en) | 2019-08-26 | 2024-02-27 | 삼성전자주식회사 | Method and apparatus of augmenting image |
CN110706200B (en) * | 2019-09-02 | 2022-08-05 | 杭州深睿博联科技有限公司 | Data prediction method and device |
CN110619391B (en) * | 2019-09-19 | 2023-04-18 | 华南理工大学 | Detection model compression method and device and computer readable storage medium |
KR102405867B1 (en) * | 2019-10-02 | 2022-06-08 | (주)디앤아이파비스 | Method, apparatus and system for determining importance of patent documents using artificial intelligence model |
KR102095892B1 (en) * | 2019-10-02 | 2020-04-01 | (주)디앤아이파비스 | Method, apparatus and system for determining similarity of patent documents using artificial intelligence model |
US11568062B2 (en) * | 2019-10-10 | 2023-01-31 | Baidu Usa Llc | Methods to protect neural network models |
KR20210062477A (en) | 2019-11-21 | 2021-05-31 | 삼성전자주식회사 | Electronic apparatus and control method thereof |
CN110929794B (en) * | 2019-11-28 | 2022-12-13 | 哈尔滨工程大学 | Side-scan sonar image classification method based on multi-task learning |
CN111028177B (en) * | 2019-12-12 | 2023-07-21 | 武汉大学 | Edge-based deep learning image motion blur removing method |
CN111179175B (en) * | 2019-12-27 | 2023-04-07 | 深圳力维智联技术有限公司 | Image processing method and device based on convolutional neural network and storage medium |
US11687778B2 (en) | 2020-01-06 | 2023-06-27 | The Research Foundation For The State University Of New York | Fakecatcher: detection of synthetic portrait videos using biological signals |
CN113111679A (en) * | 2020-01-09 | 2021-07-13 | 北京君正集成电路股份有限公司 | Design method of human-shaped upper half monitoring network structure |
KR102295202B1 (en) * | 2020-01-31 | 2021-08-27 | 중앙대학교 산학협력단 | Multiple object detection method and apparatus |
US20210248462A1 (en) * | 2020-02-07 | 2021-08-12 | Nec Laboratories America, Inc. | Interpreting convolutional sequence model by learning local and resolution-controllable prototypes |
CN111401516B (en) * | 2020-02-21 | 2024-04-26 | 华为云计算技术有限公司 | Searching method for neural network channel parameters and related equipment |
CN113496775A (en) * | 2020-03-19 | 2021-10-12 | 上海联影医疗科技股份有限公司 | Control method and system of radioactive ray equipment |
US20210295150A1 (en) * | 2020-03-20 | 2021-09-23 | Robert Bosch Gmbh | System and method for distributed neural networks on edge devices |
US11508143B2 (en) | 2020-04-03 | 2022-11-22 | Disney Enterprises, Inc. | Automated salience assessment of pixel anomalies |
US11568249B2 (en) | 2020-04-07 | 2023-01-31 | International Business Machines Corporation | Automated decision making for neural architecture search |
US11386656B2 (en) * | 2020-04-08 | 2022-07-12 | Moxa Inc. | Device and method of handling video content analysis |
US11379697B2 (en) * | 2020-05-20 | 2022-07-05 | Bank Of America Corporation | Field programmable gate array architecture for image analysis |
EP4150514A1 (en) * | 2020-06-30 | 2023-03-22 | L'Oréal | High-resolution controllable face aging with spatially-aware conditional gans |
CN111862030B (en) * | 2020-07-15 | 2024-02-09 | 北京百度网讯科技有限公司 | Face synthetic image detection method and device, electronic equipment and storage medium |
US20220028088A1 (en) * | 2020-07-23 | 2022-01-27 | Vingroup Joint Stock Company | Multi-scale segmentation system |
US10885387B1 (en) * | 2020-08-04 | 2021-01-05 | SUPERB Al CO., LTD. | Methods for training auto-labeling device and performing auto-labeling by using hybrid classification and devices using the same |
US10902291B1 (en) * | 2020-08-04 | 2021-01-26 | Superb Ai Co., Ltd. | Methods for training auto labeling device and performing auto labeling related to segmentation while performing automatic verification by using uncertainty scores and devices using the same |
US10902290B1 (en) * | 2020-08-04 | 2021-01-26 | Superb Ai Co., Ltd. | Methods for training auto labeling device and performing auto labeling related to object detection while performing automatic verification by using uncertainty scores and devices using the same |
US11563899B2 (en) * | 2020-08-14 | 2023-01-24 | Raytheon Company | Parallelization technique for gain map generation using overlapping sub-images |
US11889049B2 (en) | 2020-08-14 | 2024-01-30 | Raytheon Company | Gain map generation with rotation compensation |
CN112016432A (en) * | 2020-08-24 | 2020-12-01 | 高新兴科技集团股份有限公司 | License plate character recognition method based on deep learning, storage medium and electronic equipment |
US11978260B2 (en) | 2020-08-25 | 2024-05-07 | Axon Enterprise, Inc. | Systems and methods for rapid license plate reading |
CN112035683A (en) * | 2020-09-30 | 2020-12-04 | 北京百度网讯科技有限公司 | User interaction information processing model generation method and user interaction information processing method |
CN112215245A (en) * | 2020-11-05 | 2021-01-12 | 中国联合网络通信集团有限公司 | Image identification method and device |
CN112464009A (en) * | 2020-11-17 | 2021-03-09 | 百度(中国)有限公司 | Method and device for generating pairing image, electronic equipment and storage medium |
CN112580453A (en) * | 2020-12-08 | 2021-03-30 | 成都数之联科技有限公司 | Land use classification method and system based on remote sensing image and deep learning |
US20240056575A1 (en) * | 2020-12-22 | 2024-02-15 | Intellectual Discovery Co., Ltd. | Deep learning-based image coding method and device |
US20220198539A1 (en) * | 2020-12-23 | 2022-06-23 | Panasonic Intellectual Property Management Co., Ltd. | Checkout system and checkout method |
KR20220102420A (en) * | 2021-01-13 | 2022-07-20 | 삼성전자주식회사 | Electronic device for upscailing image and method for controlling the same |
CN112434678B (en) * | 2021-01-27 | 2021-06-04 | 成都无糖信息技术有限公司 | Face measurement feature space searching system and method based on artificial neural network |
CN113095251B (en) * | 2021-04-20 | 2022-05-27 | 清华大学深圳国际研究生院 | Human body posture estimation method and system |
US20220392209A1 (en) * | 2021-06-04 | 2022-12-08 | Apple Inc. | Object recognition |
CN113392899B (en) * | 2021-06-10 | 2022-05-10 | 电子科技大学 | Image classification method based on binary image classification network |
US11798117B2 (en) * | 2021-06-16 | 2023-10-24 | Bank Of America Corporation | Systems and methods for intelligent steganographic protection |
KR102635607B1 (en) * | 2021-11-04 | 2024-02-08 | 중앙대학교 산학협력단 | Method and apparatus for multi-label class classification based on coarse-to-fine convolutional neural network |
US11527074B1 (en) | 2021-11-24 | 2022-12-13 | Continental Automotive Technologies GmbH | Systems and methods for deep multi-task learning for embedded machine vision applications |
CN114973727B (en) * | 2022-08-02 | 2022-09-30 | 成都工业职业技术学院 | Intelligent driving method based on passenger characteristics |
Family Cites Families (49)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6990217B1 (en) * | 1999-11-22 | 2006-01-24 | Mitsubishi Electric Research Labs. Inc. | Gender classification with support vector machines |
DE60130742T2 (en) * | 2001-05-28 | 2008-07-17 | Honda Research Institute Europe Gmbh | Pattern recognition with hierarchical networks |
US7912246B1 (en) * | 2002-10-28 | 2011-03-22 | Videomining Corporation | Method and system for determining the age category of people based on facial images |
AU2003289116A1 (en) * | 2002-12-16 | 2004-07-09 | Canon Kabushiki Kaisha | Pattern identification method, device thereof, and program thereof |
US20050047647A1 (en) * | 2003-06-10 | 2005-03-03 | Ueli Rutishauser | System and method for attentional selection |
US7219085B2 (en) * | 2003-12-09 | 2007-05-15 | Microsoft Corporation | System and method for accelerating and optimizing the processing of machine learning techniques using a graphics processing unit |
JP4532915B2 (en) * | 2004-01-29 | 2010-08-25 | キヤノン株式会社 | Pattern recognition learning method, pattern recognition learning device, image input device, computer program, and computer-readable recording medium |
JP4546157B2 (en) * | 2004-06-03 | 2010-09-15 | キヤノン株式会社 | Information processing method, information processing apparatus, and imaging apparatus |
US20080292194A1 (en) * | 2005-04-27 | 2008-11-27 | Mark Schmidt | Method and System for Automatic Detection and Segmentation of Tumors and Associated Edema (Swelling) in Magnetic Resonance (Mri) Images |
US7747070B2 (en) * | 2005-08-31 | 2010-06-29 | Microsoft Corporation | Training convolutional neural networks on graphics processing units |
WO2008133951A2 (en) * | 2007-04-24 | 2008-11-06 | Massachusetts Institute Of Technology | Method and apparatus for image processing |
US8027521B1 (en) * | 2008-03-25 | 2011-09-27 | Videomining Corporation | Method and system for robust human gender recognition using facial feature localization |
US8135202B2 (en) * | 2008-06-02 | 2012-03-13 | Nec Laboratories America, Inc. | Automated method and system for nuclear analysis of biopsy images |
US8582807B2 (en) * | 2010-03-15 | 2013-11-12 | Nec Laboratories America, Inc. | Systems and methods for determining personal characteristics |
WO2012036956A1 (en) * | 2010-09-15 | 2012-03-22 | Identicoin, Inc. | Coin identification method and apparatus |
US8498491B1 (en) * | 2011-08-10 | 2013-07-30 | Google Inc. | Estimating age using multiple classifiers |
US9311564B2 (en) * | 2012-10-05 | 2016-04-12 | Carnegie Mellon University | Face age-estimation and methods, systems, and software therefor |
US9626597B2 (en) * | 2013-05-09 | 2017-04-18 | Tencent Technology (Shenzhen) Company Limited | Systems and methods for facial age identification |
US10198689B2 (en) * | 2014-01-30 | 2019-02-05 | Hrl Laboratories, Llc | Method for object detection in digital image and video using spiking neural networks |
IL231862A (en) * | 2014-04-01 | 2015-04-30 | Superfish Ltd | Neural network image representation |
US9659341B2 (en) * | 2014-06-25 | 2017-05-23 | Qualcomm Incorporated | Texture pipe as an image processing engine |
FR3025344B1 (en) * | 2014-08-28 | 2017-11-24 | Commissariat Energie Atomique | NETWORK OF CONVOLUTIONAL NEURONS |
US10255547B2 (en) * | 2014-12-04 | 2019-04-09 | Nvidia Corporation | Indirectly accessing sample data to perform multi-convolution operations in a parallel processing system |
US10168785B2 (en) * | 2015-03-03 | 2019-01-01 | Nvidia Corporation | Multi-sensor based user interface |
US9786036B2 (en) * | 2015-04-28 | 2017-10-10 | Qualcomm Incorporated | Reducing image resolution in deep convolutional networks |
US9741107B2 (en) * | 2015-06-05 | 2017-08-22 | Sony Corporation | Full reference image quality assessment based on convolutional neural network |
US10410096B2 (en) * | 2015-07-09 | 2019-09-10 | Qualcomm Incorporated | Context-based priors for object detection in images |
US9633282B2 (en) * | 2015-07-30 | 2017-04-25 | Xerox Corporation | Cross-trained convolutional neural networks using multimodal images |
US10204299B2 (en) * | 2015-11-04 | 2019-02-12 | Nec Corporation | Unsupervised matching in fine-grained datasets for single-view object reconstruction |
US9881234B2 (en) * | 2015-11-25 | 2018-01-30 | Baidu Usa Llc. | Systems and methods for end-to-end object detection |
US10095957B2 (en) * | 2016-03-15 | 2018-10-09 | Tata Consultancy Services Limited | Method and system for unsupervised word image clustering |
WO2017177367A1 (en) * | 2016-04-11 | 2017-10-19 | Xiaogang Wang | Method and system for object tracking |
US9904871B2 (en) * | 2016-04-14 | 2018-02-27 | Microsoft Technologies Licensing, LLC | Deep convolutional neural network prediction of image professionalism |
US9953679B1 (en) * | 2016-05-24 | 2018-04-24 | Gopro, Inc. | Systems and methods for generating a time lapse video |
US20170344876A1 (en) * | 2016-05-31 | 2017-11-30 | Samsung Electronics Co., Ltd. | Efficient sparse parallel winograd-based convolution scheme |
US10185891B1 (en) * | 2016-07-08 | 2019-01-22 | Gopro, Inc. | Systems and methods for compact convolutional neural networks |
US10169647B2 (en) * | 2016-07-27 | 2019-01-01 | International Business Machines Corporation | Inferring body position in a scan |
US20180060719A1 (en) * | 2016-08-29 | 2018-03-01 | International Business Machines Corporation | Scale-space label fusion using two-stage deep neural net |
US10354362B2 (en) * | 2016-09-08 | 2019-07-16 | Carnegie Mellon University | Methods and software for detecting objects in images using a multiscale fast region-based convolutional neural network |
US10360494B2 (en) * | 2016-11-30 | 2019-07-23 | Altumview Systems Inc. | Convolutional neural network (CNN) system based on resolution-limited small-scale CNN modules |
US10467458B2 (en) * | 2017-07-21 | 2019-11-05 | Altumview Systems Inc. | Joint face-detection and head-pose-angle-estimation using small-scale convolutional neural network (CNN) modules for embedded systems |
US10185895B1 (en) * | 2017-03-23 | 2019-01-22 | Gopro, Inc. | Systems and methods for classifying activities captured within images |
WO2019027505A1 (en) * | 2017-08-01 | 2019-02-07 | Apple Inc. | Face detection, pose estimation, and distance from a camera estimation using a single network |
US20190063932A1 (en) * | 2017-08-28 | 2019-02-28 | Nec Laboratories America, Inc. | Autonomous Vehicle Utilizing Pose Estimation |
US10282589B2 (en) * | 2017-08-29 | 2019-05-07 | Konica Minolta Laboratory U.S.A., Inc. | Method and system for detection and classification of cells using convolutional neural networks |
US10366166B2 (en) * | 2017-09-07 | 2019-07-30 | Baidu Usa Llc | Deep compositional frameworks for human-like language acquisition in virtual environments |
US20190079533A1 (en) * | 2017-09-13 | 2019-03-14 | TuSimple | Neural network architecture method for deep odometry assisted by static scene optical flow |
US10671083B2 (en) * | 2017-09-13 | 2020-06-02 | Tusimple, Inc. | Neural network architecture system for deep odometry assisted by static scene optical flow |
US10223610B1 (en) * | 2017-10-15 | 2019-03-05 | International Business Machines Corporation | System and method for detection and classification of findings in images |
-
2017
- 2017-02-23 US US15/441,194 patent/US10360494B2/en active Active
- 2017-07-21 US US15/657,109 patent/US10268947B2/en active Active
- 2017-10-03 US US15/724,256 patent/US10558908B2/en active Active
- 2017-11-28 CA CA2986860A patent/CA2986860A1/en not_active Abandoned
- 2017-11-28 CA CA2986863A patent/CA2986863A1/en not_active Abandoned
- 2017-11-30 KR KR1020170162650A patent/KR20180062422A/en unknown
- 2017-11-30 SG SG10201709945UA patent/SG10201709945UA/en unknown
- 2017-11-30 SG SG10201709943RA patent/SG10201709943RA/en unknown
- 2017-11-30 KR KR1020170162656A patent/KR20180062423A/en unknown
Also Published As
Publication number | Publication date |
---|---|
US10558908B2 (en) | 2020-02-11 |
CA2986863A1 (en) | 2018-05-30 |
US10360494B2 (en) | 2019-07-23 |
KR20180062422A (en) | 2018-06-08 |
CA2986860A1 (en) | 2018-05-30 |
SG10201709945UA (en) | 2018-06-28 |
US20180150740A1 (en) | 2018-05-31 |
US20180150684A1 (en) | 2018-05-31 |
US10268947B2 (en) | 2019-04-23 |
US20180150681A1 (en) | 2018-05-31 |
KR20180062423A (en) | 2018-06-08 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
SG10201709943RA (en) | A convolutional neural network (cnn) system based on resolution-limited small-scale cnn modules | |
MX2022004773A (en) | Systems and methods for structured illumination microscopy. | |
MX2020014293A (en) | Artificial intelligence-based generation of sequencing metadata. | |
MX2017009879A (en) | Batch normalization layers. | |
MY181495A (en) | Method for processing input low-resolution image to output high-resolution image | |
EP2953065A3 (en) | Generating representations of input sequences using neural networks | |
GB2566152A (en) | Methods and systems for processing point-cloud data with a line scanner | |
MX2017002593A (en) | Event stream transformations. | |
EP3153998A3 (en) | Neural network unit that performs concurrent lstm cell calculations | |
AU2018326401A1 (en) | Method and system for use in performing localisation | |
EP3107280A3 (en) | Photoelectric conversion device, image reading apparatus, image forming apparatus, and method of photoelectric conversion | |
WO2015078018A8 (en) | Method and system for face image recognition | |
TW201614583A (en) | Multi-exposure imaging system and white balance method | |
GB201305814D0 (en) | Method, system and computer program for comparing images | |
WO2018154092A8 (en) | Iterative multiscale image generation using neural networks | |
EP3614267A3 (en) | Recoverable stream processing | |
SG11201906692TA (en) | Method and electronic device for supporting artificial participation in decision-making of blockchain | |
GB2552598A (en) | Images for query answers | |
TWM533238U (en) | 360 degree panoramic camera module and apparatus | |
WO2022090178A3 (en) | Partitioned template matching and symbolic peephole optimization | |
EP3789928A3 (en) | Neural network method and apparatus | |
Halidias | Construction of positivity preserving numerical schemes for multidimensional stochastic differential equations | |
GB2572920A (en) | Camera system including lens with magnification gradient | |
PH12018501579A1 (en) | Image processing method and device | |
MX2020005800A (en) | Method for capturing haptic content in multiple communication devices. |