JP7163515B2 - ニューラルネットワークのトレーニング方法、ビデオ認識方法及び装置 - Google Patents
ニューラルネットワークのトレーニング方法、ビデオ認識方法及び装置 Download PDFInfo
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Application Number | Priority Date | Filing Date | Title |
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CN202010567864.7A CN111767985B (zh) | 2020-06-19 | 2020-06-19 | 一种神经网络的训练方法、视频识别方法及装置 |
CN202010567864.7 | 2020-06-19 | ||
PCT/CN2021/086199 WO2021253938A1 (fr) | 2020-06-19 | 2021-04-09 | Procédé et appareil d'apprentissage de réseau neuronal, et procédé et appareil de reconnaissance vidéo |
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JP2022541712A JP2022541712A (ja) | 2022-09-27 |
JP7163515B2 true JP7163515B2 (ja) | 2022-10-31 |
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JP2021570177A Active JP7163515B2 (ja) | 2020-06-19 | 2021-04-09 | ニューラルネットワークのトレーニング方法、ビデオ認識方法及び装置 |
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JP (1) | JP7163515B2 (fr) |
KR (1) | KR20220011208A (fr) |
CN (1) | CN111767985B (fr) |
TW (1) | TWI770967B (fr) |
WO (1) | WO2021253938A1 (fr) |
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CN111767985B (zh) * | 2020-06-19 | 2022-07-22 | 深圳市商汤科技有限公司 | 一种神经网络的训练方法、视频识别方法及装置 |
CN112598021A (zh) * | 2020-11-27 | 2021-04-02 | 西北工业大学 | 一种基于自动机器学习的图结构搜索方法 |
WO2024172250A1 (fr) * | 2023-02-15 | 2024-08-22 | 이화여자대학교 산학협력단 | Procédé et appareil d'allègement de réseau d'intelligence artificielle à l'aide d'un niveau de contribution |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2018520404A (ja) | 2015-04-28 | 2018-07-26 | クゥアルコム・インコーポレイテッドQualcomm Incorporated | ニューラルネットワークのためのトレーニング基準としてのフィルタ特異性 |
JP2018170003A (ja) | 2017-03-30 | 2018-11-01 | 富士通株式会社 | ビデオ中のイベントの検出装置、方法及び画像処理装置 |
JP2020052484A (ja) | 2018-09-25 | 2020-04-02 | Awl株式会社 | 物体認識カメラシステム、再学習システム、及び物体認識プログラム |
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CN104281853B (zh) * | 2014-09-02 | 2017-11-17 | 电子科技大学 | 一种基于3d卷积神经网络的行为识别方法 |
US11023523B2 (en) * | 2015-10-23 | 2021-06-01 | Carnegie Mellon University | Video content retrieval system |
US10546211B2 (en) * | 2016-07-01 | 2020-01-28 | Google Llc | Convolutional neural network on programmable two dimensional image processor |
EP3306528B1 (fr) * | 2016-10-04 | 2019-12-25 | Axis AB | Algorithmes d'analyse destines a fournir des donnees d'apprentissage a des reseaux neuronaux |
US11010658B2 (en) * | 2017-12-22 | 2021-05-18 | Intel Corporation | System and method for learning the structure of deep convolutional neural networks |
CN108228861B (zh) * | 2018-01-12 | 2020-09-01 | 第四范式(北京)技术有限公司 | 用于执行机器学习的特征工程的方法及系统 |
CN108334910B (zh) * | 2018-03-30 | 2020-11-03 | 国信优易数据股份有限公司 | 一种事件检测模型训练方法以及事件检测方法 |
CN108985259B (zh) * | 2018-08-03 | 2022-03-18 | 百度在线网络技术(北京)有限公司 | 人体动作识别方法和装置 |
CN109284820A (zh) * | 2018-10-26 | 2019-01-29 | 北京图森未来科技有限公司 | 一种深度神经网络的结构搜索方法及装置 |
US20200167659A1 (en) * | 2018-11-27 | 2020-05-28 | Electronics And Telecommunications Research Institute | Device and method for training neural network |
CN110598598A (zh) * | 2019-08-30 | 2019-12-20 | 西安理工大学 | 基于有限样本集的双流卷积神经网络人体行为识别方法 |
CN110705463A (zh) * | 2019-09-29 | 2020-01-17 | 山东大学 | 基于多模态双流3d网络的视频人体行为识别方法及系统 |
CN110852168A (zh) * | 2019-10-11 | 2020-02-28 | 西北大学 | 基于神经架构搜索的行人重识别模型构建方法及装置 |
CN111767985B (zh) * | 2020-06-19 | 2022-07-22 | 深圳市商汤科技有限公司 | 一种神经网络的训练方法、视频识别方法及装置 |
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- 2020-06-19 CN CN202010567864.7A patent/CN111767985B/zh active Active
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- 2021-04-09 WO PCT/CN2021/086199 patent/WO2021253938A1/fr active Application Filing
- 2021-04-09 KR KR1020227000769A patent/KR20220011208A/ko active Search and Examination
- 2021-04-09 JP JP2021570177A patent/JP7163515B2/ja active Active
- 2021-04-27 TW TW110115206A patent/TWI770967B/zh active
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
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JP2018520404A (ja) | 2015-04-28 | 2018-07-26 | クゥアルコム・インコーポレイテッドQualcomm Incorporated | ニューラルネットワークのためのトレーニング基準としてのフィルタ特異性 |
JP2018170003A (ja) | 2017-03-30 | 2018-11-01 | 富士通株式会社 | ビデオ中のイベントの検出装置、方法及び画像処理装置 |
JP2020052484A (ja) | 2018-09-25 | 2020-04-02 | Awl株式会社 | 物体認識カメラシステム、再学習システム、及び物体認識プログラム |
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CN111767985B (zh) | 2022-07-22 |
KR20220011208A (ko) | 2022-01-27 |
JP2022541712A (ja) | 2022-09-27 |
CN111767985A (zh) | 2020-10-13 |
WO2021253938A1 (fr) | 2021-12-23 |
TWI770967B (zh) | 2022-07-11 |
TW202201285A (zh) | 2022-01-01 |
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