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Deep Understanding of Urban Mobility from CityscapeWebcams
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Zhang, Shanghang. |
| 단체저자명 | Carnegie Mellon University. Electrical and Computer Engineering. |
| 서명/저자사항 | Deep Understanding of Urban Mobility from CityscapeWebcams. |
| 발행사항 | [S.l.] : Carnegie Mellon University., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 129 p. |
| 소장본 주기 | School code: 0041. |
| ISBN | 9780355958812 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-09(E), Section: B.
Advisers: Jose MF Moura |
| 이용제한사항 | This item is not available from ProQuest Dissertations & Theses. |
| 요약 | Deep understanding of urban mobility is of great significance for many real-world applications, such as urban traffic management and autonomous driving. This thesis develops deep learning methodologies to extract vehicle counts from streaming re |
| 일반주제명 | Computer engineering. Artificial intelligence. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-09B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998516 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00024090 | DP 621.3 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출불가(별치) |
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