[IPOL announce] new article: A Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing
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Wed Sep 16 10:54:57 CEST 2015
A new article is available in IPOL: http://www.ipol.im/pub/art/2015/137/
Yi-Qing Wang, and Nicolas Limare,
A Fast C++ Implementation of Neural Network Backpropagation Training
Algorithm: Application to Bayesian Optimal Image Demosaicing,
Image Processing On Line, 5 (2015), pp. 257–266.
http://dx.doi.org/10.5201/ipol.2015.137
Abstract
Recent years have seen a surge of interest in multilayer neural networks
fueled by their successful applications in numerous image processing and
computer vision tasks. In this article, we describe a C++ implementation
of the stochastic gradient descent to train a multilayer neural network,
where a fast and accurate acceleration of tanh(·) is achieved with
linear interpolation. As an example of application, we present a neural
network able to deliver state-of-the-art performance in image demosaicing.
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