673 citations · 1k across the 10 of their papers we have counts for
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cs.CV2015
ReSeg: A Recurrent Neural Network-based Model for Semantic Segmentation
Francesco Visin, Marco Ciccone, Adriana Romero +5
We propose a structured prediction architecture, which exploits the local generic features extracted by Convolutional Neural Networks and the capacity of Recurrent Neural Networks…
cs.CV2015★ 232 cited
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks
Francesco Visin, Kyle Kastner, Kyunghyun Cho +3
In this paper, we propose a deep neural network architecture for object recognition based on recurrent neural networks. The proposed network, called ReNet, replaces the ubiquitous…