A novel active learning method in relevance feedback for content-based remote sensing image retrieval

IEEE Transactions on Geoscience and Remote Sensing

Volumn 53, Issue 5, 2015, Pages 2323-2334

  Demir, Begum ^a   Bruzzone, Lorenzo ^a  

^a UNIVERSITY OF TRENTO   (Italy)

Author keywords

Active learning (AL); content based image retrieval (CBIR); relevance feedback (RF); remote sensing (RS)

Indexed keywords

ALUMINUM; ARTIFICIAL INTELLIGENCE; CONTENT BASED RETRIEVAL; DIGITAL STORAGE; FEEDBACK; IMAGE RECONSTRUCTION; REMOTE SENSING; SPACE OPTICS;

ACTIVE LEARNING; ACTIVE LEARNING METHODS; CONTENT-BASED IMAGE RETRIEVAL; RELEVANCE FEEDBACK; REMOTE SENSING IMAGE RETRIEVAL; REMOTE SENSING IMAGES; SUPPORT VECTOR MACHINE CLASSIFIERS; UNDERLYING DISTRIBUTION;

IMAGE RETRIEVAL;

CLUSTER ANALYSIS; LEARNING; REMOTE SENSING; SATELLITE IMAGERY; UNCERTAINTY ANALYSIS;

EID: 84921031076     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2014.2358804     Document Type: Article

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