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Learning, Moving, and Predicting with Global Motion Representations
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Learning, Moving, and Predicting with Global Motion Representations. |
| 개인저자 | Jaegle, Andrew. |
| 단체저자명 | University of Pennsylvania. Neuroscience. |
| 발행사항 | [S.l.]: University of Pennsylvania., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 135 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-10B(E). Dissertation Abstract International |
| ISBN | 9780438037113 |
| 학위논문주기 | Thesis (Ph.D.)--University of Pennsylvania, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-10(E), Section: B.
Adviser: Kostas Daniilidis. |
| 요약 | In order to effectively respond to and influence the world they inhabit, animals and other intelligent agents must understand and predict the state of the world and its dynamics. An agent that can characterize how the world moves is better equip |
| 일반주제명 | Neurosciences. Computer science. Artificial intelligence. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
