most citedModeling Information Flow Through Deep Neural Networks

3 citations · 3 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2019

Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma

Ahmad Chaddad, Saima Rathore, Mingli Zhang +2

This paper proposes to use deep radiomic features (DRFs) from a convolutional neural network (CNN) to model fine-grained texture signatures in the radiomic analysis of recurrent gl…

cs.LG2017★ 3 cited

Modeling Information Flow Through Deep Neural Networks

Ahmad Chaddad, Behnaz Naisiri, Marco Pedersoli +3

This paper proposes a principled information theoretic analysis of classification for deep neural network structures, e.g. convolutional neural networks (CNN). The output of convol…