Artificial intelligence for maximizing content based image retrieval
Artificial intelligence for maximizing content based image retrieval [electronic resource] /
Zongmin Ma, editor
- Hershey, Pa. : Information Science Reference, c2009
Includes bibliographical references and index
Genetic algorithms and other approaches in image feature extraction and representation -- Improving image retrieval by clustering -- Review on texture feature extraction and description methods in content-based medical image retrieval -- Content-based image classification and retrieval: a rule-based system using rough sets framework -- Content based image retrieval using active-nets -- Content-based image retrieval: from the object detection/recognition point of view -- Making image retrieval and classification more accurate using time series and learned constraints -- A machine learning-based model for content-based image retrieval -- Solving the small and asymmetric sampling problem in the context of image retrieval -- Content analysis from user's relevance feedback for content-based image retrieval -- Preference extraction in image retrieval -- Personalized content-based image retrieval -- A semantics sensitive framework of organization and retrieval for multimedia databases -- Content-based retrieval for mammograms -- Event detection, query, and retrieval for video surveillance -- MMIR: an advanced content-based image retrieval system using a hierarchical learning framework.
Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field
Electronic reproduction.
Farmington Hills, Mi :
Gale.
Available via World Wide Web
Mode of access: Internet
9781605661759 (e-book) 9781605661742
Artificial intelligence
Image processing
Includes bibliographical references and index
Genetic algorithms and other approaches in image feature extraction and representation -- Improving image retrieval by clustering -- Review on texture feature extraction and description methods in content-based medical image retrieval -- Content-based image classification and retrieval: a rule-based system using rough sets framework -- Content based image retrieval using active-nets -- Content-based image retrieval: from the object detection/recognition point of view -- Making image retrieval and classification more accurate using time series and learned constraints -- A machine learning-based model for content-based image retrieval -- Solving the small and asymmetric sampling problem in the context of image retrieval -- Content analysis from user's relevance feedback for content-based image retrieval -- Preference extraction in image retrieval -- Personalized content-based image retrieval -- A semantics sensitive framework of organization and retrieval for multimedia databases -- Content-based retrieval for mammograms -- Event detection, query, and retrieval for video surveillance -- MMIR: an advanced content-based image retrieval system using a hierarchical learning framework.
Discusses major aspects of content-based image retrieval (CBIR) using current technologies and applications within the artificial intelligence (AI) field
Electronic reproduction.
Farmington Hills, Mi :
Gale.
Available via World Wide Web
Mode of access: Internet
9781605661759 (e-book) 9781605661742
Artificial intelligence
Image processing