Protected Pooling Method of Sparse Coding in Visual Classification
نویسندگان
چکیده
Sparse Coding, a popular feature coding method, has shown superior performance in visual recognition tasks. Different pooling methods, such as average pooling and max pooling, are commonly employed after feature coding. However, it has not been explained clearly what characteristic accounts for the success of pooling method. In this paper, a new pooling method, namely protected pooling, is proposed. Our method produces features putting more emphasis on weak codes. What’s more, we prove that all other pooling methods follow the same rules. Experiments on Scene 15, Caltech-101 and Flowers 17 demonstrate our improvements.
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