SG11202103717QA - Method and device for training deep model, electronic equipment, and storage medium - Google Patents

Method and device for training deep model, electronic equipment, and storage medium

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Publication number
SG11202103717QA
SG11202103717QA SG11202103717QA SG11202103717QA SG11202103717QA SG 11202103717Q A SG11202103717Q A SG 11202103717QA SG 11202103717Q A SG11202103717Q A SG 11202103717QA SG 11202103717Q A SG11202103717Q A SG 11202103717QA SG 11202103717Q A SG11202103717Q A SG 11202103717QA
Authority
SG
Singapore
Prior art keywords
storage medium
electronic equipment
training deep
deep model
training
Prior art date
Application number
SG11202103717QA
Inventor
Jiahui Li
Original Assignee
Beijing Sensetime Technology Development Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Sensetime Technology Development Co Ltd filed Critical Beijing Sensetime Technology Development Co Ltd
Publication of SG11202103717QA publication Critical patent/SG11202103717QA/en

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    • 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
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • 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
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • 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
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/12—Edge-based segmentation
    • 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
    • G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
    • 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
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/774—Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
    • 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
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/69—Microscopic objects, e.g. biological cells or cellular parts
    • 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
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10056—Microscopic image
    • 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
    • G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
    • 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
    • G06T2207/20081—Training; Learning
    • 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
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20096—Interactive definition of curve of interest
    • 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
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20104—Interactive definition of region of interest [ROI]
    • 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
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V2201/00—Indexing scheme relating to image or video recognition or understanding
    • G06V2201/03—Recognition of patterns in medical or anatomical images

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Artificial Intelligence (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • Molecular Biology (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Databases & Information Systems (AREA)
  • Mathematical Physics (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Biodiversity & Conservation Biology (AREA)
  • Image Analysis (AREA)
SG11202103717QA 2018-12-29 2019-10-30 Method and device for training deep model, electronic equipment, and storage medium SG11202103717QA (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201811646736.0A CN109740668B (en) 2018-12-29 2018-12-29 Deep model training method and device, electronic equipment and storage medium
PCT/CN2019/114497 WO2020134533A1 (en) 2018-12-29 2019-10-30 Method and apparatus for training deep model, electronic device, and storage medium

Publications (1)

Publication Number Publication Date
SG11202103717QA true SG11202103717QA (en) 2021-05-28

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Country Status (7)

Country Link
US (1) US20210224598A1 (en)
JP (1) JP7110493B2 (en)
KR (1) KR20210042364A (en)
CN (1) CN109740668B (en)
SG (1) SG11202103717QA (en)
TW (1) TWI747120B (en)
WO (1) WO2020134533A1 (en)

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CN109740668B (en) * 2018-12-29 2021-03-30 北京市商汤科技开发有限公司 Deep model training method and device, electronic equipment and storage medium
CN110909688B (en) * 2019-11-26 2020-07-28 南京甄视智能科技有限公司 Face detection small model optimization training method, face detection method and computer system
CN113515980B (en) * 2020-05-20 2022-07-05 阿里巴巴集团控股有限公司 Model training method, device, equipment and storage medium
CN111738197B (en) * 2020-06-30 2023-09-05 中国联合网络通信集团有限公司 Training image information processing method and device
WO2022251684A1 (en) * 2021-05-28 2022-12-01 Visa International Service Association Metamodel and feature generation for rapid and accurate anomaly detection
CN113947771B (en) * 2021-10-15 2023-06-27 北京百度网讯科技有限公司 Image recognition method, apparatus, device, storage medium, and program product
EP4227908A1 (en) * 2022-02-11 2023-08-16 Zenseact AB Iterative refinement of annotated datasets
CN114764874B (en) * 2022-04-06 2023-04-07 北京百度网讯科技有限公司 Deep learning model training method, object recognition method and device
CN115600112B (en) * 2022-11-23 2023-03-07 北京结慧科技有限公司 Method, device, equipment and medium for obtaining behavior prediction model training set

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GB216635A (en) * 1923-04-12 1924-06-05 Reginald Mosley Tayler An improved amusement device
SG179302A1 (en) * 2010-09-16 2012-04-27 Advanced Material Engineering Pte Ltd Projectile with strike point marking
CN104346622A (en) * 2013-07-31 2015-02-11 富士通株式会社 Convolutional neural network classifier, and classifying method and training method thereof
US9633282B2 (en) * 2015-07-30 2017-04-25 Xerox Corporation Cross-trained convolutional neural networks using multimodal images
CN105389584B (en) * 2015-10-13 2018-07-10 西北工业大学 Streetscape semanteme marking method based on convolutional neural networks with semantic transfer conjunctive model
CN105550651B (en) * 2015-12-14 2019-12-24 中国科学院深圳先进技术研究院 Automatic analysis method and system for panoramic image of digital pathological section
CN105931226A (en) * 2016-04-14 2016-09-07 南京信息工程大学 Automatic cell detection and segmentation method based on deep learning and using adaptive ellipse fitting
CN106096531B (en) * 2016-05-31 2019-06-14 安徽省云力信息技术有限公司 A kind of traffic image polymorphic type vehicle checking method based on deep learning
CN106202997B (en) * 2016-06-29 2018-10-30 四川大学 A kind of cell division detection method based on deep learning
CN106157308A (en) * 2016-06-30 2016-11-23 北京大学 Rectangular target object detecting method
CN107392125A (en) * 2017-07-11 2017-11-24 中国科学院上海高等研究院 Training method/system, computer-readable recording medium and the terminal of model of mind
CN107967491A (en) * 2017-12-14 2018-04-27 北京木业邦科技有限公司 Machine learning method, device, electronic equipment and the storage medium again of plank identification
CN108021903B (en) * 2017-12-19 2021-11-16 南京大学 Error calibration method and device for artificially labeling leucocytes based on neural network
CN108074243B (en) * 2018-02-05 2020-07-24 志诺维思（北京）基因科技有限公司 Cell positioning method and cell segmentation method
CN108615236A (en) * 2018-05-08 2018-10-02 上海商汤智能科技有限公司 A kind of image processing method and electronic equipment
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CN109087306A (en) * 2018-06-28 2018-12-25 众安信息技术服务有限公司 Arteries iconic model training method, dividing method, device and electronic equipment
CN109740668B (en) * 2018-12-29 2021-03-30 北京市商汤科技开发有限公司 Deep model training method and device, electronic equipment and storage medium

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Publication number Publication date
CN109740668B (en) 2021-03-30
US20210224598A1 (en) 2021-07-22
CN109740668A (en) 2019-05-10
TW202042181A (en) 2020-11-16
WO2020134533A1 (en) 2020-07-02
KR20210042364A (en) 2021-04-19
JP7110493B2 (en) 2022-08-01
JP2021536083A (en) 2021-12-23
TWI747120B (en) 2021-11-21

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