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Computer Vision and Deep Learning with Applications to Object Detection, Segmentation, and Document Analysis
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Computer Vision and Deep Learning with Applications to Object Detection, Segmentation, and Document Analysis. |
| 개인저자 | Du, Xianzhi. |
| 단체저자명 | University of Maryland, College Park. Electrical Engineering. |
| 발행사항 | [S.l.]: University of Maryland, College Park., 2017. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2017. |
| 형태사항 | 137 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-11B(E). Dissertation Abstract International |
| ISBN | 9780438139770 |
| 학위논문주기 | Thesis (Ph.D.)--University of Maryland, College Park, 2017. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Advisers: Larry Davis |
| 요약 | There are three work on signature matching for document analysis. In the first work, we propose a large-scale signature matching method based on locality sensitive hashing (LSH). Shape Context features are used to describe the structure of signa |
| 요약 | There are three work on deep learning for object detection and segmentation. In the first work, we propose a deep neural network fusion architecture for fast and robust pedestrian detection. The proposed network fusion architecture allows for pa |
| 일반주제명 | Artificial intelligence. Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
