| LDR | | 02344nam u200409 4500 |
| 001 | | 000000418659 |
| 005 | | 20190215163038 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438402140 |
| 035 | |
▼a (MiAaPQ)AAI10845004 |
| 035 | |
▼a (MiAaPQ)umd:19349 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Singh, Bharat. |
| 245 | 10 |
▼a Detecting Objects and Actions with Deep Learning. |
| 260 | |
▼a [S.l.]:
▼b University of Maryland, College Park.,
▼c 2018. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2018. |
| 300 | |
▼a 115 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-02(E), Section: B. |
| 500 | |
▼a Adviser: Larry S. Davis. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Maryland, College Park, 2018. |
| 520 | |
▼a Deep learning based visual recognition and localization is one of the pillars of computer vision and is the driving force behind applications like self-driving cars, visual search, video surveillance, augmented reality, to name a few. This thesi |
| 520 | |
▼a In the first part, an analysis of different techniques for recognizing and detecting objects under extreme scale variation is presented. Since small and large objects are difficult to recognize at smaller and larger scales of an image pyramid re |
| 520 | |
▼a Next, we present a real-time large-scale object detector (R-FCN-3000) for detecting thousands of classes where objectness detection and classification are decoupled. To obtain the detection score for an RoI, we multiply the objectness score with |
| 520 | |
▼a Finally, we present a multi-stream bi-directional recurrent neural network for action detection. This was the first deep learning based system which could perform action localization in long videos and it could do it just with RGB data, without |
| 590 | |
▼a School code: 0117. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a University of Maryland, College Park.
▼b Computer Science. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 80-02B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0117 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000030
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a ***1012033 |