Semi-supervised Image Classification Learning Based on Random Feature Subspace

Liu Li; Zhang Hua-xiang; Xiaojun Hu; Feifei Sun

doi:10.1007/978-3-662-45646-0_24

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Semi-supervised Image Classification Learning Based on Random Feature Subspace

Liu Li Zhang Hua-xiang Xiaojun Hu Feifei Sun

Year: 2014 Communications in computer and information science Pages: 237-242 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-662-45646-0_24

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Keywords:

Pattern recognition (psychology) Artificial intelligence Subspace topology Computer science Linear subspace Feature vector Gabor filter Feature (linguistics) Robustness (evolution) Support vector machine Entropy (arrow of time) Random forest Contextual image classification Image texture Feature extraction Image (mathematics) Mathematics Image processing

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Topics

Remote Sensing and Land Use

Physical Sciences → Earth and Planetary Sciences → Atmospheric Science

Image Retrieval and Classification Techniques

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Image Processing Techniques and Applications

Physical Sciences → Engineering → Media Technology

Semi-supervised Image Classification Learning Based on Random Feature Subspace

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