A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval

• Main Authors: LIU, Yang, JIN, Rong, Mummert, Lily, Sukthankar, Rahul, Goode, Adam, ZHENG, Bin, HOI, Steven C. H., Satyanarayanan, Mahadev
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2010
• Subjects: Boosting; Distance Metric Learning; Image/video retrieval; Machine learning; boosting; distance metric learning; image retrieval; Artificial Intelligence and Robotics; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/2315; https://ink.library.smu.edu.sg/context/sis_research/article/3315/viewcontent/A_Boosting_Framework_for_Visuality_Preserving_Dist.pdf
• Institution: Singapore Management University

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learni...