Using Similarity between Paired Instances to Improve Multiple-Instance Learning via Embedded Instance Selection

Duzhou Zhang; Xibin Cao

doi:10.1007/978-3-642-42042-9_44

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Using Similarity between Paired Instances to Improve Multiple-Instance Learning via Embedded Instance Selection

Duzhou Zhang Xibin Cao

Year: 2013 Lecture notes in computer science Pages: 352-359 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-642-42042-9_44

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Keywords:

Computer science Artificial intelligence Machine learning Classifier (UML) Benchmark (surveying) Similarity (geometry) Selection (genetic algorithm) Feature selection Set (abstract data type) Data mining

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Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Image and Video Retrieval Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Video Analysis and Summarization

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Using Similarity between Paired Instances to Improve Multiple-Instance Learning via Embedded Instance Selection

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