Unsupervised detection of regions of interest using iterative link analysis
This paper proposes a fast and scalable alternating optimization technique to detect regions of interest (ROIs) in cluttered Web images without labels. The proposed approach discovers highly probable regions of object instances by iteratively repeating the following two functions: (1) choose the...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Neural Information Processing Systems Foundation
2011
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| Online Access: | http://hdl.handle.net/1721.1/64744 https://orcid.org/0000-0003-4915-0256 |