A Theoretical Analysis of Feature Pooling in Visual Recognition A Theoretical Analysis of Feature Pooling in Visual Recognition
Paper summary This paper analyzes max pooling and average pooling, as it is used in many convolutional neural networks (CNNs). ## Why pooling is used * invariance to image transformations * more compact representations (- remove irrelevant information) * better robustness to noise and clutter ## Max pooling or average pooling? No clear answer to that. Sometimes one seems to be better, sometimes the other, sometimes something in between.
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A Theoretical Analysis of Feature Pooling in Visual Recognition
Boureau, Y-Lan and Ponce, Jean and LeCun, Yann
International Conference on Machine Learning - 2010 via Bibsonomy
Keywords: dblp


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