- 专利标题: LEARNING METHOD AND TESTING METHOD FOR R-CNN BASED OBJECT DETECTOR, AND LEARNING DEVICE AND TESTING DEVICE USING THE SAME
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申请号: EP19184961.1申请日: 2019-07-08
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公开(公告)号: EP3633550A1公开(公告)日: 2020-04-08
- 发明人: Kim, Kye-Hyeon , Kim, Yongjoong , Kim, Insu , Kim, Hak-Kyoung , Nam, Woonhyun , Boo, SukHoon , Sung, Myungchul , Yeo, Donghun , Ryu, Wooju , Jang, Taewoong , Jeong, Kyungjoong , Je, Hongmo , Cho, Hojin
- 申请人: Stradvision, Inc.
- 申请人地址: No. 4427, 4 research bldg. RIST 67, Cheongam-ro Nam-Gu Pohang, Gyeongsangbuk 37673 KR
- 专利权人: Stradvision, Inc.
- 当前专利权人: Stradvision, Inc.
- 当前专利权人地址: No. 4427, 4 research bldg. RIST 67, Cheongam-ro Nam-Gu Pohang, Gyeongsangbuk 37673 KR
- 代理机构: V.O.
- 优先权: US201816151693 20181004
- 主分类号: G06K9/62
- IPC分类号: G06K9/62 ; G06K9/32 ; G06N3/04 ; G06N3/08
摘要:
A method for learning parameters of an object detector based on R-CNN is provided. The method includes steps of: a learning device (a) if training image is acquired, instructing (i) convolutional layers to generate feature maps by applying convolution operations to the training image, (ii) an RPN to output ROI regression information and matching information (iii) a proposal layer to output ROI candidates as ROI proposals by referring to the ROI regression information and the matching information, and (iv) a proposal-selecting layer to output the ROI proposals by referring to the training image; (b) instructing pooling layers to generate feature vectors by pooling regions in the feature map, and instructing FC layers to generate object regression information and object class information; and (c) instructing first loss layers to calculate and backpropagate object class loss and object regression loss, to thereby learn parameters of the FC layers and the convolutional layers.
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