Efficient anchor graph hashing with data-dependent anchor selection

Hiroaki Takebe, Yusuke Uehara, Seiichi Uchida

研究成果: Contribution to journalArticle査読

2 被引用数 (Scopus)

抄録

Anchor graph hashing (AGH) is a promising hashing method for nearest neighbor (NN) search. AGH realizes efficient search by generating and utilizing a small number of points that are called anchors. In this paper, we propose a method for improving AGH, which considers data distribution in a similarity space and selects suitable anchors by performing principal component analysis (PCA) in the similarity space.

本文言語英語
ページ(範囲)2030-2033
ページ数4
ジャーナルIEICE Transactions on Information and Systems
E98D
11
DOI
出版ステータス出版済み - 11 2015

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

フィンガープリント 「Efficient anchor graph hashing with data-dependent anchor selection」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル