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
Other languages
English (en)
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 (zh) 2018-12-29 2018-12-29 深度模型训练方法及装置、电子设备及存储介质
PCT/CN2019/114497 WO2020134533A1 (zh) 2018-12-29 2019-10-30 深度模型训练方法及装置、电子设备及存储介质

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 (zh)
JP (1) JP7110493B2 (zh)
KR (1) KR20210042364A (zh)
CN (1) CN109740668B (zh)
SG (1) SG11202103717QA (zh)
TW (1) TWI747120B (zh)
WO (1) WO2020134533A1 (zh)

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CN109740668B (zh) * 2018-12-29 2021-03-30 北京市商汤科技开发有限公司 深度模型训练方法及装置、电子设备及存储介质
CN110909688B (zh) * 2019-11-26 2020-07-28 南京甄视智能科技有限公司 人脸检测小模型优化训练方法、人脸检测方法及计算机系统
CN113515980B (zh) * 2020-05-20 2022-07-05 阿里巴巴集团控股有限公司 模型训练方法、装置、设备和存储介质
CN111738197B (zh) * 2020-06-30 2023-09-05 中国联合网络通信集团有限公司 一种训练图像信息处理的方法和装置
CN113591893B (zh) * 2021-01-26 2024-06-28 腾讯医疗健康(深圳)有限公司 基于人工智能的图像处理方法、装置和计算机设备
CN117396901A (zh) * 2021-05-28 2024-01-12 维萨国际服务协会 用于快速且准确的异常检测的元模型和特征生成
CN113947771B (zh) * 2021-10-15 2023-06-27 北京百度网讯科技有限公司 图像识别方法、装置、设备、存储介质以及程序产品
EP4227908A1 (en) * 2022-02-11 2023-08-16 Zenseact AB Iterative refinement of annotated datasets
CN114627343A (zh) * 2022-03-14 2022-06-14 北京百度网讯科技有限公司 深度学习模型的训练方法、图像处理方法、装置及设备
CN114764874B (zh) * 2022-04-06 2023-04-07 北京百度网讯科技有限公司 深度学习模型的训练方法、对象识别方法和装置
CN115600112B (zh) * 2022-11-23 2023-03-07 北京结慧科技有限公司 获取行为预测模型训练集的方法、装置、设备及介质

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CN104346622A (zh) * 2013-07-31 2015-02-11 富士通株式会社 卷积神经网络分类器及其分类方法和训练方法
US9633282B2 (en) * 2015-07-30 2017-04-25 Xerox Corporation Cross-trained convolutional neural networks using multimodal images
CN105389584B (zh) * 2015-10-13 2018-07-10 西北工业大学 基于卷积神经网络与语义转移联合模型的街景语义标注方法
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CN109740668B (zh) * 2018-12-29 2021-03-30 北京市商汤科技开发有限公司 深度模型训练方法及装置、电子设备及存储介质

Also Published As

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

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