자료유형 | 학위논문 |
---|---|
서명/저자사항 | Crowd-Driven Computer Vision. |
개인저자 | Tuite, Kathleen . |
단체저자명 | University of Washington. Computer Science and Engineering. |
발행사항 | [S.l.]: University of Washington., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 163 p. |
기본자료 저록 | Dissertations Abstracts International 81-03B. Dissertation Abstract International |
ISBN | 9781085717687 |
학위논문주기 | Thesis (Ph.D.)--University of Washington, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-03, Section: B.
Advisor: Shapiro, Linda. |
이용제한사항 | This item must not be sold to any third party vendors.This item must not be added to any third party search indexes. |
요약 | 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 |
일반주제명 | Computer science. |
언어 | 영어 |
바로가기 | ![]() |