Relevance feedback based on active learning and GMM in image retrieval system.
Shuo WangJianjian WangPublished in: ICMLC (2014)
Keyphrases
- relevance feedback
- active learning
- gaussian mixture model
- image retrieval systems
- information retrieval systems
- query expansion
- document retrieval
- user feedback
- low level features
- learning strategies
- image retrieval
- web image retrieval
- supervised learning
- semi supervised learning
- retrieval effectiveness
- learning algorithm
- selective sampling
- mixture model
- random sampling
- training examples
- speaker recognition
- em algorithm
- relevant documents
- retrieval model
- semi supervised
- gaussian mixture modeling
- training set
- experimental design
- machine learning
- gaussian mixture
- unlabeled data
- background subtraction
- image search
- cost sensitive
- cbir systems
- text retrieval
- labeled data
- expectation maximization
- feature vectors
- user system interaction
- pool based active learning
- image collections
- feature weighting
- query refinement
- learning process
- active learning strategies
- voice activity detection