가야대학교 분성도서관

상단 글로벌/추가 메뉴

회원 로그인

주메뉴

: • 전체검색; • 단행본; • 정기간행물; • 학위논문; • 비도서; • 특정번호 검색; • 기사색인; • 학습연구지원; • 지정도서

: • 전자자원통합검색; • 해외 WEB DB; • E-Book; • E-Learning; • 국내 WEB DB; • 인터넷검색

: • 대출현황조회/연장; • 예약현황조회/취소; • 희망도서; • 내서재; • 나의서평; • 나의태그; • 나의위젯; • RSS; • SDI; • 개인정보관리

: • 공지사항; • FAQ; • Q&A 일반·학술; • 신착/인기 도서; • 학위논문온라인제출; • 외부인 이용안내; • 설문조사

: • 도서관 소개; • 연혁; • 현황; • 이용안내; • 찾아오시는 길

자료검색

Home
상세정보

상세정보

검색결과 돌아가기

부가기능

MARC보기

Finding Objects in Complex Scenes

상세 프로파일

상세정보
자료유형	E-Book
개인저자	Sun, Jin.
단체저자명	University of Maryland, College Park. Computer Science.
서명/저자사항	Finding Objects in Complex Scenes.
발행사항	[S.l.] : University of Maryland, College Park., 2018
발행사항	Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항	175 p.
소장본 주기	School code: 0117.
ISBN	9780438402317
일반주기	Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. Adviser: David Jacobs.
요약	Object detection is one of the fundamental problems in computer vision that has great practical impact. Current object detectors work well under certain conditions. However, challenges arise when scenes become more complex. Scenes are often clut
요약	We believe the key to tackle those challenges is to understand the rich context of objects in scenes, which includes: the appearance variations of an object due to viewpoint and lighting condition changes
요약	To facilitate collecting training data with large variations, we design a novel user interface, ARLabeler, utilizing the power of Augmented Reality (AR) devices. Instead of labeling images from the Internet passively, we put an observer in the r
요약	We also study challenges in deploying object detectors in real world scenes: detecting curb ramps in street view images. A system, Tohme, is proposed to combine detection results from detectors and human crowdsourcing verifications. One core com
요약	One of the insights from Tohme is that context is crucial in detecting objects. To understand the complex relationship between objects and their environment, we propose a standalone context model that predicts where an object can occur in an ima
요약	To take a step beyond single object based detections, we explicitly model the geometrical relationships between groups of objects and use the layout information to represent scenes as a whole. We show that such a strategy is useful in retrieving
일반주제명	Computer science.
언어	영어
기본자료 저록	Dissertation Abstracts International80-02B(E). Dissertation Abstract International
대출바로가기	http://www.riss.kr/pdu/ddodLink.do?id=T15000096