南京信息工程大学学报2017，Vol.9Issue(6)：567-574,8.DOI:10.13878/j.cnki.jnuist.2017.06.001
基于用户点击数据的细粒度图像识别方法概述
A survey of fine-grained image recognition based on user click data
摘要
Abstract
In recent years,fine-grained image recognition has become a hotspot in computer vision area.Due to the subtle visual differences among different image categories and the serious semantic gap,the performance of traditional image recognition algorithms for fine-grained images recognition is mostly unsatisfactory.To overcome these challenges,many researchers have been concentrating on image recognition with user click data. This paper focuses on the three key modules of the fine-grained recognition system with user click data:data preprocessing,feature extracting and model construction.Also,existing algorithms for click data based image recognition are summarized,and the related latest progresses are demonstrated.关键词
用户点击/图像识别/度量学习/深度学习/语义鸿沟Key words
user click data/image recognition/metric learning/deep learning/semantic gap分类
信息技术与安全科学引用本文复制引用
俞俊,谭敏,张宏源,张海超..基于用户点击数据的细粒度图像识别方法概述[J].南京信息工程大学学报,2017,9(6):567-574,8.基金项目
国家自然科学基金优秀青年基金(61622205) （61622205）
国家自然科学基金青年基金(61602136) （61602136）
