Convolutional neural network

Known as: Max norm constraint, Convolutional neural networks, ConvNet 
In machine learning, a convolutional neural network (CNN, or ConvNet) is a type of feed-forward artificial neural network in which the connectivity… (More)
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Topic mentions per year

1970-2018
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Papers overview

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Review
2018
Review
2018
In the last few years, deep learning has lead to very good performance on a variety of problems, such as object recognition… (More)
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Highly Cited
2016
Highly Cited
2016
We propose two efficient approximations to standard convolutional neural networks: Binary-Weight-Networks and XNOR-Networks. In… (More)
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Highly Cited
2015
Highly Cited
2015
MatConvNet is an open source implementation of Convolutional Neural Networks (CNNs) with a deep integration in the MATLAB… (More)
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Highly Cited
2014
Highly Cited
2014
The ability to accurately represent sentences is central to language understanding. We describe a convolutional architecture… (More)
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Highly Cited
2014
Highly Cited
2014
Convolutional Neural Networks (CNNs) have been established as a powerful class of models for image recognition problems… (More)
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Highly Cited
2014
Highly Cited
2014
We report on a series of experiments with convolutional neural networks (CNN) trained on top of pre-trained word vectors for… (More)
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Highly Cited
2014
Highly Cited
2014
Convolutional neural networks (CNN) have recently shown outstanding image classification performance in the large- scale visual… (More)
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Highly Cited
2014
Highly Cited
2014
Recently, the hybrid deep neural network (DNN)- hidden Markov model (HMM) has been shown to significantly improve speech… (More)
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Highly Cited
2012
Highly Cited
2012
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC… (More)
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Highly Cited
1997
Highly Cited
1997
We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines… (More)
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