TY - JOUR
T1 - Advances in machine learning and deep neural networks
AU - Chellappa, Rama
AU - Theodoridis, Sergios
AU - van Schaik, Andre
PY - 2021
Y1 - 2021
N2 - This special issue covers promising developments in the related areas of machine learning (ML) and deep neural networks (NNs) and offers possible paths for the future. Deep neural networks (NNs) have offered performances much beyond of the incremental nature as compared to previous techniques. The scope of this issue is to put together a number of papers, written by world experts in the field, that try to provide some answers, to the possible extent, to the previously discussed problems, and at the same time to summarize research that has been carried in the related areas. The topics covered range from theory and algorithms to applications and hardware implementations.
AB - This special issue covers promising developments in the related areas of machine learning (ML) and deep neural networks (NNs) and offers possible paths for the future. Deep neural networks (NNs) have offered performances much beyond of the incremental nature as compared to previous techniques. The scope of this issue is to put together a number of papers, written by world experts in the field, that try to provide some answers, to the possible extent, to the previously discussed problems, and at the same time to summarize research that has been carried in the related areas. The topics covered range from theory and algorithms to applications and hardware implementations.
UR - https://hdl.handle.net/1959.7/uws:60650
U2 - 10.1109/JPROC.2021.3072172
DO - 10.1109/JPROC.2021.3072172
M3 - Article
SN - 0018-9219
VL - 109
SP - 607
EP - 611
JO - Proceedings of the IEEE
JF - Proceedings of the IEEE
IS - 5
ER -