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» Evaluating Image Retrieval
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MM
2009
ACM
209views Multimedia» more  MM 2009»
14 years 2 months ago
Brain state decoding for rapid image retrieval
Human visual perception is able to recognize a wide range of targets under challenging conditions, but has limited throughput. Machine vision and automatic content analytics can p...
Jun Wang, Eric Pohlmeyer, Barbara Hanna, Yu-Gang J...
PRICAI
2010
Springer
13 years 6 months ago
Layered Hypernetwork Models for Cross-Modal Associative Text and Image Keyword Generation in Multimodal Information Retrieval
Conventional methods for multimodal data retrieval use text-tag based or cross-modal approaches such as tag-image co-occurrence and canonical correlation analysis. Since there are ...
JungWoo Ha, Byoung-Hee Kim, Bado Lee, Byoung-Tak Z...
CVPR
2008
IEEE
14 years 10 months ago
Semi-supervised distance metric learning for Collaborative Image Retrieval
Typical content-based image retrieval (CBIR) solutions with regular Euclidean metric usually cannot achieve satisfactory performance due to the semantic gap challenge. Hence, rele...
Steven C. H. Hoi, Wei Liu, Shih-Fu Chang
ICASSP
2007
IEEE
14 years 2 months ago
Integrating Relevance Feedback in Boosting for Content-Based Image Retrieval
Many content-based image retrieval applications suffer from small sample set and high dimensionality problems. Relevance feedback is often used to alleviate those problems. In thi...
Jie Yu, Yijuan Lu, Yuning Xu, Nicu Sebe, Qi Tian
ECIR
1998
Springer
13 years 9 months ago
Social and Cognitive Factors in the Design and Evaluation of Multimedia Systems
Multimedia information retrieval systems design is currently considered a complex task since it requires an understanding of users specific way of searching, processing and using ...
Silvia Gabrielli