Deep fisher kernels - End to end learning of the fisher kernel GMM parameters

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 1402-1409

  Sydorov, Vladyslav ^a   Sakurada, Mayu ^a   Lampert, Christoph H ^a  

^a INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA   (Austria)

Author keywords

deep learning; Fisher kernel; Gaussian mixture models; image classification; support vector machines

Indexed keywords

BIOINFORMATICS; DEEP LEARNING; FEEDFORWARD NEURAL NETWORKS; GAUSSIAN DISTRIBUTION; GRADIENT METHODS; IMAGE CLASSIFICATION; LARGE DATASET; LEARNING SYSTEMS; NETWORK LAYERS; OBJECT RECOGNITION; SUPPORT VECTOR MACHINES; VECTORS;

BIOLOGICAL ANALOGIES; CLASSIFICATION ACCURACY; DATA REPRESENTATIONS; FISHER KERNELS; GAUSSIAN MIXTURE MODEL; MULTI-LAYER FEED-FORWARD NETWORKS; STATISTICAL LEARNING THEORY; SUPPORT VECTOR MACHINE CLASSIFIERS;

LEARNING ALGORITHMS;

EID: 84911395964     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.182     Document Type: Conference Paper

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