Small sample learning during multimedia retrieval using BiasMap

By Xiang Sean Zhou, Thomas S. Huang. Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001, 2001

331 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

View Paper: https://www.semanticscholar.org/paper/637fd567b10046d1b5b3f1462592d8a9d7e8ba40

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Dacheng Tao
2. Luc Van Gool
3. Xiaogang Wang
4. Shuicheng Yan
5. Ming-Hsuan Yang
6. Trevor Darrell
7. Xiaoou Tang
8. Yi Yang

In Signal Processing

1. Dacheng Tao
2. Shuicheng Yan
3. Xuelong Li
4. Jia Li
5. Zhengjun Zha
6. Tat-seng Chua
7. Wei-Ying Ma
8. Michael S. Lew

Citations in the corpus

• Attribute feedback (2012, methodology): “[31] Y. Yang, Y. Yang, Z. Huang, H. Shen, and F. Nie.”
• Asymmetric bagging and random subspace for support vector machines-based relevance feedback in image retrieval (2006, background): “Zhou and Huang [32] also proposed an (1 + x)-class classification in which there is an unknown number of classes but the user only concerns one class (positive feedback samples).”
• Image retrieval: Ideas, influences, and trends of the new age (2008, background): “While most algorithms treat RF as a two-class problem, it is often intuitive to consider multiple groups of images as relevant or irrelevant [Hoi and Lyu 2004a; Nakazato et al. 2003; Zhou and Huang 2001a].”
• Image and Video Retrieval (2003, methodology): “2 [25] H. Miyamori.”