14 citations · 20 across the 9 of their papers we have counts for
3 papers · 1 filter
An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network
Nathan Hubens, Matei Mancas, Bernard Gosselin +2
In recent years, deep neural networks have known a wide success in various application domains. However, they require important computational and memory resources, which severely h…
DeepRare: Generic Unsupervised Visual Attention Models
Phutphalla Kong, Matei Mancas, Bernard Gosselin +1
Human visual system is modeled in engineering field providing feature-engineered methods which detect contrasted/surprising/unusual data into images. This data is "interesting" for…
One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget
Nathan Hubens, Matei Mancas, Bernard Gosselin +2
Introducing sparsity in a neural network has been an efficient way to reduce its complexity while keeping its performance almost intact. Most of the time, sparsity is introduced us…