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A State-of-the-Art Survey on Deep Learning Theory and Archi..:
Md Zahangir Alom
;
Tarek M. Taha
;
Chris Yakopcic
...
Computer Science & Engineering. , 2019
Link:
https://doi.org/10.3390/electronics8030292
RT Journal T1
A State-of-the-Art Survey on Deep Learning Theory and Architectures
UL https://suche.suub.uni-bremen.de/peid=base-ftmdpi:oai:mdpi.com:_2079-9292_8_3_292_&Exemplar=1&LAN=DE A1 Md Zahangir Alom A1 Tarek M. Taha A1 Chris Yakopcic A1 Stefan Westberg A1 Paheding Sidike A1 Mst Shamima Nasrin A1 Mahmudul Hasan A1 Brian C. Van Essen A1 Abdul A. S. Awwal A1 Vijayan K. Asari PB Multidisciplinary Digital Publishing Institute YR 2019 K1 deep learning K1 convolutional neural network (CNN) K1 recurrent neural network (RNN) K1 auto-encoder (AE) K1 restricted Boltzmann machine (RBM) K1 deep belief network (DBN) K1 generative adversarial network (GAN) K1 deep reinforcement learning (DRL) K1 transfer learning JF Computer Science & Engineering LK http://dx.doi.org/https://doi.org/10.3390/electronics8030292 DO https://doi.org/10.3390/electronics8030292 SF ELIB - SuUB Bremen
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