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ICANN
2010
Springer
13 years 5 months ago
Evaluation of Pooling Operations in Convolutional Architectures for Object Recognition
Abstract. A common practice to gain invariant features in object recognition models is to aggregate multiple low-level features over a small neighborhood. However, the differences ...
Dominik Scherer, Andreas Müller, Sven Behnke
CVPR
2010
IEEE
14 years 1 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...
CVPR
2011
IEEE
12 years 11 months ago
Proposal Generation for Object Detection using Cascaded Ranking SVMs
Object recognition has made great strides recently. However, the best methods, such as those based on kernelSVMs are highly computationally intensive. The problem of how to accele...
Ziming Zhang, Jonathan Warrell, Philip Torr
CVPR
2009
IEEE
14 years 11 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...