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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… 
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Related topics

Related topics

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Activation functionAlphaGoApache SparkArtificial neural network

Broader (1)

Computational neuroscience

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2019
2019
Rank-consistent Ordinal Regression for Neural Networks
In many real-world predictions tasks, class labels include information about the relative ordering between labels, which is not… 
2017
2017
Natural scene text detection with MC-MR candidate extraction and coarse-to-fine filtering
2017
2017
Introduction to Convolutional Neural Networks
6 The convolution layer 11 6.1 What is convolution? . . . . . . . . . . . . . . . . . . . . . . . . . 11 6.2 Why to convolve… 
2015
2015
Instance-Level Segmentation with Deep Densely Connected MRFs
Our aim is to provide a pixel-level object instance labeling of a monocular image. We build on recent work [27] that trained a… 
Highly Cited
2014
Highly Cited
2014
Metric Learning Based Structural Appearance Model for Robust Visual Tracking
Appearance modeling is a key issue for the success of a visual tracker. Sparse representation based appearance modeling has… 
2011
2011
A Refined Performance Characterization of Longest-Queue-First Policy in Wireless Networks
One of the major challenges in wireless networking is how to optimize the link scheduling decisions under interference… 
Review
2008
Review
2008
Spatial Regression for Marked Point Processes
In a wide range of applications, dependence on smoothly-varying covariates leads spatial point count intensities to feature… 
2000
2000
A Fast Hough Transform for the Parametrisation of Straight Lines using Fourier Methods
The Hough transform is a useful technique in the detection of straight lines and curves in an image. Due to the mathematical… 
1997
1997
Bayes inference for S-shaped software-reliability growth models
Bayes inference for a nonhomogeneous Poisson process with an S-shaped mean value function is studied. In particular, the authors… 
Highly Cited
1995
Highly Cited
1995
Classifier and shift-invariant automatic target recognition neural networks
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