Active Learning in Very Large Image Databases

@inproceedings{PandaActiveLI,
  title={Active Learning in Very Large Image Databases},
  author={Navneet Panda and Kingshy Goh and Edward Y. Chang}
}
Query-by-example and query-by-keyword both suffer from the problem of “aliasing,” meaning that example-images and keywords potentially have variable interpretations or multiple semantics. For discerning the appropriate semantic for a given query, we have established that combining active learning with kernel methods is a very effective approach. In this work, we first examine active-learning strategies, and then focus on addressing the challenges of two scalability issues: scalability in… CONTINUE READING