CN109002832A - 一种基于分层特征提取的图像识别方法 - Google Patents
一种基于分层特征提取的图像识别方法 Download PDFInfo
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- CN109002832A CN109002832A CN201810597123.6A CN201810597123A CN109002832A CN 109002832 A CN109002832 A CN 109002832A CN 201810597123 A CN201810597123 A CN 201810597123A CN 109002832 A CN109002832 A CN 109002832A
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- 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
- G06V10/46—Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
- G06V10/462—Salient features, e.g. scale invariant feature transforms [SIFT]
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24133—Distances to prototypes
- G06F18/24137—Distances to cluster centroïds
- G06F18/2414—Smoothing the distance, e.g. radial basis function networks [RBFN]
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CN109002832A true CN109002832A (zh) | 2018-12-14 |
CN109002832B CN109002832B (zh) | 2021-11-19 |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120281921A1 (en) * | 2011-05-02 | 2012-11-08 | Los Alamos National Security, Llc | Image alignment |
CN103208001A (zh) * | 2013-02-06 | 2013-07-17 | 华南师范大学 | 结合形状自适应邻域和纹理特征提取的遥感图像处理方法 |
CN104657717A (zh) * | 2015-02-12 | 2015-05-27 | 合肥工业大学 | 一种基于分层核稀疏表示的行人检测方法 |
CN105447441A (zh) * | 2015-03-19 | 2016-03-30 | 北京天诚盛业科技有限公司 | 人脸认证方法和装置 |
US20160307071A1 (en) * | 2015-04-20 | 2016-10-20 | Xerox Corporation | Fisher vectors meet neural networks: a hybrid visual classification architecture |
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2018
- 2018-06-11 CN CN201810597123.6A patent/CN109002832B/zh active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120281921A1 (en) * | 2011-05-02 | 2012-11-08 | Los Alamos National Security, Llc | Image alignment |
CN103208001A (zh) * | 2013-02-06 | 2013-07-17 | 华南师范大学 | 结合形状自适应邻域和纹理特征提取的遥感图像处理方法 |
CN104657717A (zh) * | 2015-02-12 | 2015-05-27 | 合肥工业大学 | 一种基于分层核稀疏表示的行人检测方法 |
CN105447441A (zh) * | 2015-03-19 | 2016-03-30 | 北京天诚盛业科技有限公司 | 人脸认证方法和装置 |
US20160307071A1 (en) * | 2015-04-20 | 2016-10-20 | Xerox Corporation | Fisher vectors meet neural networks: a hybrid visual classification architecture |
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Effective date of registration: 20221221 Address after: 101300 room 818-030, building 1, yard 3, Jinhang East Road, Shunyi District, Beijing (Tianzhu comprehensive free trade zone) Patentee after: Interstellar Digital Technology Co.,Ltd. Address before: Room 213, Building 9, No. 30, Mengxiyuan Lane, Jingkou District, Zhenjiang City, Jiangsu Province, 212000 Patentee before: Jiangsu Qingyun Technology Consulting Service Co.,Ltd. Effective date of registration: 20221221 Address after: Room 213, Building 9, No. 30, Mengxiyuan Lane, Jingkou District, Zhenjiang City, Jiangsu Province, 212000 Patentee after: Jiangsu Qingyun Technology Consulting Service Co.,Ltd. Address before: 430062 368 Friendship Avenue, Wuchang District, Wuhan, Hubei. Patentee before: Hubei University |