Multistage committees of deep feedforward convolutional sparse denoise autoencoder for object recognition

Deep learning and unsupervised feature learning systems are known to achieve good performance in benchmarks by using extremely large architectures with many features at each layer. However, we found that the number of features' contribution to performance is very small when it is more than the...

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Vydané v:	2015 Chinese Automation Congress (CAC) s. 565 - 570
Hlavní autori:	Shicao Luo, Yongsheng Ding, Kuangrong Hao
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 01.11.2015
Predmet:	Convolution deep learning Encoding Feature extraction Kernel multistage classifiers Noise reduction object recognition Robustness sparse denoise autoencoder Training
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