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Reduction of DNNs in edge computing
[post]
2022
unpublished
Application of Deep Neural Networks (DNN) in Edge Computing has emerged as a consequence of the need of real time and distributed response of different devices in a large number of scenarios. For this end, shredding these original structures is urgent due to the high number of parameters needed to represent them. As a consequence, the most representative components of different layers are kept in order to maintain the network's accuracy as close as possible from the entire network's ones. To do
doi:10.21203/rs.3.rs-1862445/v1
fatcat:s46emoxdk5bvpkzkx2taaz7skm