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Learning Conditional Models for Visual Perception
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Veit, Andreas. |
| 단체저자명 | Cornell University. Computer Science. |
| 서명/저자사항 | Learning Conditional Models for Visual Perception. |
| 발행사항 | [S.l.] : Cornell University., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 125 p. |
| 소장본 주기 | School code: 0058. |
| ISBN | 9780438026872 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Serge J. Belongie. |
| 요약 | In recent years, the field of computer vision has seen a series of major advances, made possible by rapid development in algorithms, data collection and computing infrastructure. As a result, vision systems have started to be broadly adopted in |
| 요약 | In this dissertation, we address this limitation by building conditional vision models that can learn from multiple points of view and adapt their results to account for different conditions. First, we address the related tasks of image tagging |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-10B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998204 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00027621 | 004 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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