SG11201913365WA - Semantic segmentation model trainingmethods and apparatuses, electronic devices, and storage media - Google Patents
Semantic segmentation model trainingmethods and apparatuses, electronic devices, and storage mediaInfo
- Publication number
- SG11201913365WA SG11201913365WA SG11201913365WA SG11201913365WA SG11201913365WA SG 11201913365W A SG11201913365W A SG 11201913365WA SG 11201913365W A SG11201913365W A SG 11201913365WA SG 11201913365W A SG11201913365W A SG 11201913365WA SG 11201913365W A SG11201913365W A SG 11201913365WA
- Authority
- SG
- Singapore
- Prior art keywords
- trainingmethods
- apparatuses
- electronic devices
- storage media
- semantic segmentation
- Prior art date
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06N3/084—Backpropagation, e.g. using gradient descent
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
- G06F18/217—Validation; Performance evaluation; Active pattern learning techniques
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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 OR CALCULATING; 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
- G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/26—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion
- G06V10/267—Segmentation of patterns in the image field; Cutting or merging of image elements to establish the pattern region, e.g. clustering-based techniques; Detection of occlusion by performing operations on regions, e.g. growing, shrinking or watersheds
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
- G06V30/19147—Obtaining sets of training patterns; Bootstrap methods, e.g. bagging or boosting
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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 OR CALCULATING; 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
- G06V30/26—Techniques for post-processing, e.g. correcting the recognition result
- G06V30/262—Techniques for post-processing, e.g. correcting the recognition result using context analysis, e.g. lexical, syntactic or semantic context
- G06V30/274—Syntactic or semantic context, e.g. balancing
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- Data Mining & Analysis (AREA)
- Artificial Intelligence (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Computing Systems (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Multimedia (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Mathematical Physics (AREA)
- Biomedical Technology (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medical Informatics (AREA)
- Databases & Information Systems (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710648545.7A CN108229479B (zh) | 2017-08-01 | 2017-08-01 | 语义分割模型的训练方法和装置、电子设备、存储介质 |
| PCT/CN2018/097549 WO2019024808A1 (zh) | 2017-08-01 | 2018-07-27 | 语义分割模型的训练方法和装置、电子设备、存储介质 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| SG11201913365WA true SG11201913365WA (en) | 2020-01-30 |
Family
ID=62654687
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| SG11201913365WA SG11201913365WA (en) | 2017-08-01 | 2018-07-27 | Semantic segmentation model trainingmethods and apparatuses, electronic devices, and storage media |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US11301719B2 (enExample) |
| JP (1) | JP6807471B2 (enExample) |
| KR (1) | KR102358554B1 (enExample) |
| CN (1) | CN108229479B (enExample) |
| SG (1) | SG11201913365WA (enExample) |
| WO (1) | WO2019024808A1 (enExample) |
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| US10755142B2 (en) * | 2017-09-05 | 2020-08-25 | Cognizant Technology Solutions U.S. Corporation | Automated and unsupervised generation of real-world training data |
| CN110012210B (zh) * | 2018-01-05 | 2020-09-22 | Oppo广东移动通信有限公司 | 拍照方法、装置、存储介质及电子设备 |
| CN110622213B (zh) * | 2018-02-09 | 2022-11-15 | 百度时代网络技术(北京)有限公司 | 利用3d语义地图进行深度定位和分段的系统和方法 |
| CN109101878B (zh) * | 2018-07-01 | 2020-09-29 | 浙江工业大学 | 一种用于秸秆燃值估计的图像分析系统及图像分析方法 |
| CN109084955A (zh) * | 2018-07-02 | 2018-12-25 | 北京百度网讯科技有限公司 | 显示屏质量检测方法、装置、电子设备及存储介质 |
| CN109190631A (zh) * | 2018-08-31 | 2019-01-11 | 阿里巴巴集团控股有限公司 | 图片的目标对象标注方法及装置 |
| CN109087708B (zh) * | 2018-09-20 | 2021-08-31 | 深圳先进技术研究院 | 用于斑块分割的模型训练方法、装置、设备及存储介质 |
| JP6695947B2 (ja) | 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 | 固体撮像システム、画像処理方法及びプログラム |
| CN109241951A (zh) * | 2018-10-26 | 2019-01-18 | 北京陌上花科技有限公司 | 色情图片识别方法、识别模型构建方法及识别模型和计算机可读存储介质 |
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| US9836641B2 (en) * | 2014-12-17 | 2017-12-05 | Google Inc. | Generating numeric embeddings of images |
| JP6993334B2 (ja) * | 2015-11-29 | 2022-01-13 | アーテリーズ インコーポレイテッド | 自動化された心臓ボリュームセグメンテーション |
| CN105787482A (zh) * | 2016-02-26 | 2016-07-20 | 华北电力大学 | 一种基于深度卷积神经网络的特定目标轮廓图像分割方法 |
| US9704257B1 (en) * | 2016-03-25 | 2017-07-11 | Mitsubishi Electric Research Laboratories, Inc. | System and method for semantic segmentation using Gaussian random field network |
| CN106022221B (zh) | 2016-05-09 | 2021-11-30 | 腾讯科技(深圳)有限公司 | 一种图像处理方法及处理系统 |
| JP2018097807A (ja) * | 2016-12-16 | 2018-06-21 | 株式会社デンソーアイティーラボラトリ | 学習装置 |
| JP7203844B2 (ja) * | 2017-07-25 | 2023-01-13 | 達闥機器人股▲分▼有限公司 | トレーニングデータの生成方法、生成装置及びその画像のセマンティックセグメンテーション方法 |
| CN108229479B (zh) * | 2017-08-01 | 2019-12-31 | 北京市商汤科技开发有限公司 | 语义分割模型的训练方法和装置、电子设备、存储介质 |
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