佐藤優伍, 福里司, 森島繁生
印象選択による対話型画像検索システムの提案
画像電子学会 VCワークショップ2017
http://www.mlab.phys.waseda.ac.jp/conferences/vcws2017/index.html
This paper presents a novel image retrieval system for finding a particular image from a database using the implicit similarity of impression. Previous content-based image retrieval systems depend on the low-level visual features of images (e.g., luminance or RGB color), so it is difficult to compute semantic image similarity Download the surface recovery image. Additionally, if a user does not have much knowledge about a target image, these systems may be difficult to use because they require some image or text queries House download made with a card. To solve these problems, we integrate the deep convolutional neural network and online learning based on relevance feedback to interactively estimate the image the user is searching for 안드로이드 한글 파일명. We ran user studies with 10 subjects on a public database consisting of 597 face images, and confirmed that the proposed system is effective for retrieving face images easily and quickly ebs 방송 다운로드.