| LDR | | 00000nam u2200205 4500 |
| 001 | | 000000432428 |
| 005 | | 20200224130110 |
| 008 | | 200131s2019 ||||||||||||||||| ||eng d |
| 020 | |
▼a 9781085717687 |
| 035 | |
▼a (MiAaPQ)AAI13899888 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 247004 |
| 082 | 0 |
▼a 004 |
| 100 | 1 |
▼a Tuite, Kathleen . |
| 245 | 10 |
▼a Crowd-Driven Computer Vision. |
| 260 | |
▼a [S.l.]:
▼b University of Washington.,
▼c 2019. |
| 260 | 1 |
▼a Ann Arbor:
▼b ProQuest Dissertations & Theses,
▼c 2019. |
| 300 | |
▼a 163 p. |
| 500 | |
▼a Source: Dissertations Abstracts International, Volume: 81-03, Section: B. |
| 500 | |
▼a Advisor: Shapiro, Linda. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Washington, 2019. |
| 506 | |
▼a This item must not be sold to any third party vendors. |
| 506 | |
▼a This item must not be added to any third party search indexes. |
| 520 | |
▼a Artificial intelligence and machine learning are rapidly advancing the ability of computers to see, listen, understand, and interact in the real world. Data is crucial to training these systems, and the quality of the data, the source of the data, and how it is collected and labeled are as important as the data itself for building systems that are effective, robust, and ethical. Computer vision, as a subset of machine learning dealing visual processing, is at a point where there are powerful algorithms and ample computing power, but there is a bottleneck of high quality labeled data available to train these algorithms. At the same time, there is an untapped source of data available |
| 590 | |
▼a School code: 0250. |
| 650 | 4 |
▼a Computer science. |
| 690 | |
▼a 0984 |
| 710 | 20 |
▼a University of Washington.
▼b Computer Science and Engineering. |
| 773 | 0 |
▼t Dissertations Abstracts International
▼g 81-03B. |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0250 |
| 791 | |
▼a Ph.D. |
| 792 | |
▼a 2019 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15492125
▼n KERIS
▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
| 980 | |
▼a 202002
▼f 2020 |
| 990 | |
▼a ***1008102 |
| 991 | |
▼a E-BOOK |