Online learning to rank for content-based image retrieval

• Main Authors: WAN, Ji, WU, Pengcheng, HOI, Steven C. H., ZHAO, Peilin, GAO, Xingyu, WANG, Dayong, ZHANG, Yongdong., LI, Jintao
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/2932; https://ink.library.smu.edu.sg/context/sis_research/article/3932/viewcontent/IJCAI_2015_323_OnlineLearningRankContentBasedIR.pdf
• Institution: Singapore Management University

A major challenge in Content-Based Image Retrieval (CBIR) is to bridge the semantic gap between low-level image contents and high-level semantic concepts. Although researchers have investigated a variety of retrieval techniques using different types of features and distance functions, no single best...