| 翻訳と辞書 |
| LEVAN (Search Engine) ： ウィキペディア英語版 |
LEVAN (Search Engine)
The LEVAN (Learning EVerything About ANything) is a visual processing search engine developed by computer scientists from Allen Institute for Artificial Intelligence in Seattle and the University of Washington. It is capable of teaching itself about any visual concept without any human supervision during the operation. LEVAN learns which terms are relevant by analyzing the content of the images found on the Web and identifying characteristic patterns across them using recognition algorithms. The funds for the research on LEVAN was provided by the U.S. Office of Naval Research and the National Science Foundation. It was initially rolled out in March and as of 21 June 2014, users can browse a library of about 175 concepts with it.
== Operation ==
LEVAN works by associating the textual data with visual data. After providing it with a textual entry, the programme then searches through numerous books and images and identifies every possible variations of the concept and displays the results as a detailed list of images that have uniformity in appearance. The research team proposed two main approaches, called axes. The "everything" axis corresponds to every possible appearance variations of a concept, while the "anything" axis corresponds to the span of different concepts for which visual models are to be learned. A different algorithm is responsible for refining words that do not correspond to the visual data.
As of June 2014, the system has been working as an archive.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
■ウィキペディアで「LEVAN (Search Engine)」の詳細全文を読む
スポンサード リンク
| 翻訳と辞書 : 翻訳のためのインターネットリソース |
Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.
|
|