Going deeper with convolutions

We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14). The main hallmark of this architecture is the improved utilization of the...

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Vydané v:	2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) s. 1 - 9
Hlavní autori:	Szegedy, Christian, Wei Liu, Yangqing Jia, Sermanet, Pierre, Reed, Scott, Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, Rabinovich, Andrew
Médium:	Konferenčný príspevok.. Journal Article
Jazyk:	English
Vydavateľské údaje:	IEEE 01.06.2015
Predmet:	Architecture (computers) Classification Computation Computer architecture Computer vision Conferences Constants Convolutional codes Networks Neural networks Object detection Pattern recognition Sparse matrices Visualization
ISSN:	1063-6919, 1063-6919
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