SG11201903591QA - Fast computation of a convolutional neural network - Google Patents
Fast computation of a convolutional neural networkInfo
- Publication number
- SG11201903591QA SG11201903591QA SG11201903591QA SG11201903591QA SG11201903591QA SG 11201903591Q A SG11201903591Q A SG 11201903591QA SG 11201903591Q A SG11201903591Q A SG 11201903591QA SG 11201903591Q A SG11201903591Q A SG 11201903591QA SG 11201903591Q A SG11201903591Q A SG 11201903591QA
- Authority
- SG
- Singapore
- Prior art keywords
- neural network
- convolutional neural
- fast computation
- computation
- fast
- Prior art date
Links
Classifications
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- 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
-
- 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
- G06N3/06—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
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding, deleting or silencing nodes or connections
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- Molecular Biology (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Computational Linguistics (AREA)
- Mathematical Physics (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Neurology (AREA)
- Medical Informatics (AREA)
- Biodiversity & Conservation Biology (AREA)
- Databases & Information Systems (AREA)
- Human Computer Interaction (AREA)
- Oral & Maxillofacial Surgery (AREA)
- Bioinformatics & Computational Biology (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| PCT/CN2018/111655 WO2020082263A1 (en) | 2018-10-24 | 2018-10-24 | Fast computation of convolutional neural network |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| SG11201903591QA true SG11201903591QA (en) | 2020-05-28 |
Family
ID=66850328
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| SG11201903591QA SG11201903591QA (en) | 2018-10-24 | 2018-10-24 | Fast computation of a convolutional neural network |
Country Status (14)
| Country | Link |
|---|---|
| US (1) | US10635951B1 (ru) |
| EP (1) | EP3662414A4 (ru) |
| JP (1) | JP6798021B1 (ru) |
| KR (1) | KR102141324B1 (ru) |
| CN (1) | CN110537193A (ru) |
| AU (1) | AU2018353930B2 (ru) |
| BR (1) | BR112019008055B1 (ru) |
| CA (1) | CA3040685C (ru) |
| MX (1) | MX2019004654A (ru) |
| PH (1) | PH12019500889A1 (ru) |
| RU (1) | RU2722473C1 (ru) |
| SG (1) | SG11201903591QA (ru) |
| WO (1) | WO2020082263A1 (ru) |
| ZA (1) | ZA201902547B (ru) |
Families Citing this family (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10990648B2 (en) * | 2017-08-07 | 2021-04-27 | Intel Corporation | System and method for an optimized winograd convolution accelerator |
| US11494608B2 (en) * | 2019-08-14 | 2022-11-08 | Intel Corporation | Methods and apparatus to tile walk a tensor for convolution operations |
| US11657282B2 (en) * | 2019-09-16 | 2023-05-23 | Qualcomm Incorporated | Efficient inferencing with fast pointwise convolution |
| CN112766471B (zh) * | 2019-11-01 | 2024-03-29 | 中科寒武纪科技股份有限公司 | 运算装置及相关产品 |
| CN112784206A (zh) * | 2019-11-01 | 2021-05-11 | 中科寒武纪科技股份有限公司 | winograd卷积运算方法、装置、设备及存储介质 |
| US20210216868A1 (en) * | 2020-01-08 | 2021-07-15 | Maxim Integrated Products, Inc. | Systems and methods for reducing memory requirements in neural networks |
| CN111294512A (zh) * | 2020-02-10 | 2020-06-16 | 深圳市铂岩科技有限公司 | 图像处理方法、装置、存储介质及摄像装置 |
| CN111475775B (zh) * | 2020-04-14 | 2023-09-15 | 腾讯科技（深圳）有限公司 | 图形处理器的数据处理方法、文本处理方法、装置和设备 |
| CN111415000B (zh) * | 2020-04-29 | 2024-03-22 | Oppo广东移动通信有限公司 | 卷积神经网络、基于卷积神经网络的数据处理方法和装置 |
| CN111580828B (zh) * | 2020-04-30 | 2021-08-27 | 腾讯科技（深圳）有限公司 | 机器学习模型的编译优化方法和装置 |
| CN111553466B (zh) * | 2020-04-30 | 2024-03-22 | 上海商汤智能科技有限公司 | 信息处理方法、装置及设备 |
| US11687336B2 (en) * | 2020-05-08 | 2023-06-27 | Black Sesame Technologies Inc. | Extensible multi-precision data pipeline for computing non-linear and arithmetic functions in artificial neural networks |
| CN111767964A (zh) * | 2020-07-08 | 2020-10-13 | 福州大学 | 基于改进的DenseNet的多通道特征重标记图像分类方法 |
| JP2022018997A (ja) * | 2020-07-17 | 2022-01-27 | ソニーセミコンダクタソリューションズ株式会社 | 固体撮像素子、撮像装置、および、情報処理システム |
| WO2022064901A1 (ja) * | 2020-09-28 | 2022-03-31 | 富士フイルム株式会社 | 学習済みモデル変換方法、推論方法、学習済みモデル変換装置、学習済みモデル、及び推論装置 |
| WO2022119466A1 (en) * | 2020-12-01 | 2022-06-09 | Huawei Technologies Co., Ltd. | Device and method for implementing a tensor-train decomposition operation |
| JP7420100B2 (ja) | 2021-03-15 | 2024-01-23 | オムロン株式会社 | 処理装置、処理方法、およびプログラム |
| KR20220162971A (ko) * | 2021-06-02 | 2022-12-09 | 세메스 주식회사 | 데이터 처리 방법 및 데이터 비교 방법 |
| CN117495833B (zh) * | 2023-11-16 | 2024-05-28 | 广州思沛医药科技股份有限公司 | 一种基于大数据的脑卒中预测方法、系统及存储介质 |
Family Cites Families (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2872502C (en) * | 2012-05-04 | 2021-05-18 | Rearden, Llc | System and methods for coping with doppler effects in distributed-input distributed-output wireless systems |
| WO2016132150A1 (en) | 2015-02-19 | 2016-08-25 | Magic Pony Technology Limited | Enhancing visual data using and augmenting model libraries |
| US10403269B2 (en) * | 2015-03-27 | 2019-09-03 | Google Llc | Processing audio waveforms |
| CN105740894B (zh) * | 2016-01-28 | 2020-05-29 | 北京航空航天大学 | 一种高光谱遥感图像的语义标注方法 |
| US20170344876A1 (en) * | 2016-05-31 | 2017-11-30 | Samsung Electronics Co., Ltd. | Efficient sparse parallel winograd-based convolution scheme |
| CN106407986B (zh) * | 2016-08-29 | 2019-07-19 | 电子科技大学 | 一种基于深度模型的合成孔径雷达图像目标识别方法 |
| GB2554711B (en) * | 2016-10-06 | 2020-11-25 | Imagination Tech Ltd | Buffer addressing for a convolutional neural network |
| US10230725B2 (en) * | 2016-10-24 | 2019-03-12 | Sonicwall Inc. | Edge protection for internal identity providers |
| US10482155B2 (en) * | 2016-12-30 | 2019-11-19 | Intel Corporation | Winograd algorithm on a matrix processing architecture |
| RU2651147C1 (ru) * | 2017-03-27 | 2018-04-18 | Акционерное общество "ЭЛВИС-НеоТек" | Устройство и способ каскадной обработки потока изображений с помощью свёрточных нейронных сетей |
| US10467795B2 (en) * | 2017-04-08 | 2019-11-05 | Intel Corporation | Sub-graph in frequency domain and dynamic selection of convolution implementation on a GPU |
| CN107480707B (zh) * | 2017-07-26 | 2020-08-07 | 天津大学 | 一种基于信息无损池化的深度神经网络方法 |
| US10990648B2 (en) * | 2017-08-07 | 2021-04-27 | Intel Corporation | System and method for an optimized winograd convolution accelerator |
| KR102452953B1 (ko) * | 2017-10-30 | 2022-10-11 | 삼성전자주식회사 | 뉴럴 네트워크의 컨볼루션 연산을 수행하는 방법 및 장치 |
| CN107844833A (zh) * | 2017-11-28 | 2018-03-27 | 郑州云海信息技术有限公司 | 一种卷积神经网络的数据处理方法、装置及介质 |
| US10372787B2 (en) * | 2017-12-12 | 2019-08-06 | Facebook, Inc. | Hardware accelerator pre-configured with coefficients for matrix-transform operations |
-
2018
- 2018-10-24 CA CA3040685A patent/CA3040685C/en active Active
- 2018-10-24 SG SG11201903591QA patent/SG11201903591QA/en unknown
- 2018-10-24 EP EP18867295.0A patent/EP3662414A4/en not_active Withdrawn
- 2018-10-24 CN CN201880017855.1A patent/CN110537193A/zh active Pending
- 2018-10-24 KR KR1020197011555A patent/KR102141324B1/ko active IP Right Grant
- 2018-10-24 RU RU2019111961A patent/RU2722473C1/ru active
- 2018-10-24 MX MX2019004654A patent/MX2019004654A/es unknown
- 2018-10-24 AU AU2018353930A patent/AU2018353930B2/en active Active
- 2018-10-24 BR BR112019008055-4A patent/BR112019008055B1/pt active IP Right Grant
- 2018-10-24 JP JP2019521684A patent/JP6798021B1/ja active Active
- 2018-10-24 WO PCT/CN2018/111655 patent/WO2020082263A1/en unknown
-
2019
- 2019-04-22 US US16/390,042 patent/US10635951B1/en active Active
- 2019-04-23 ZA ZA2019/02547A patent/ZA201902547B/en unknown
- 2019-04-24 PH PH12019500889A patent/PH12019500889A1/en unknown
Also Published As
| Publication number | Publication date |
|---|---|
| CA3040685C (en) | 2020-07-28 |
| JP2021501377A (ja) | 2021-01-14 |
| EP3662414A1 (en) | 2020-06-10 |
| AU2018353930B2 (en) | 2020-10-08 |
| KR102141324B1 (ko) | 2020-08-05 |
| CA3040685A1 (en) | 2020-04-28 |
| EP3662414A4 (en) | 2020-07-22 |
| AU2018353930A1 (en) | 2020-05-14 |
| WO2020082263A1 (en) | 2020-04-30 |
| BR112019008055B1 (pt) | 2022-02-01 |
| MX2019004654A (es) | 2022-05-04 |
| KR20200049695A (ko) | 2020-05-08 |
| CN110537193A (zh) | 2019-12-03 |
| BR112019008055A2 (pt) | 2021-05-18 |
| US10635951B1 (en) | 2020-04-28 |
| US20200134400A1 (en) | 2020-04-30 |
| PH12019500889A1 (en) | 2019-06-17 |
| ZA201902547B (en) | 2021-02-24 |
| JP6798021B1 (ja) | 2020-12-09 |
| RU2722473C1 (ru) | 2020-06-01 |
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