자료유형 | E-Book |
---|---|
개인저자 | Wang, Chen. |
단체저자명 | Cornell University. Computer Science. |
서명/저자사항 | Persistency Algorithms for Efficient Inference in Markov Random Fields. |
발행사항 | [S.l.] : Cornell University., 2018 |
발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
형태사항 | 222 p. |
소장본 주기 | School code: 0058. |
ISBN | 9780438344464 |
일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Ramin Zabih. |
요약 | Markov Random Fields (MRFs) have achieved great success in a variety of computer vision problems, including image segmentation, stereo estimation, optical flow and image denoising, during the past 20 years. Despite the inference problem being NP |
요약 | In particular, we will explore two different lines of research. The first direction focuses on generalizing the sufficient local condition to check persistency on a set of variables as opposed to a single variable in previous works, and provides |
요약 | This thesis will present a literature study of persistency used for MRF inference, the mathematical formalization of the algorithms and the experimental results for both the first-order and higher-order MRF inference problems. |
일반주제명 | Computer science. |
언어 | 영어 |
기본자료 저록 | Dissertation Abstracts International80-01B(E). Dissertation Abstract International |
대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T15000889 |
인쇄
No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
---|---|---|---|---|---|---|---|---|
1 | WE00025797 | DP 004 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출불가(별치) |