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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… Expand
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Related topics

Related topics

50 relations
Activation functionAlphaGoApache SparkArtificial neural network
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Broader (1)

Computational neuroscience

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Review
2020
Review
2020
Deep Learning for Video Game Playing
In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of… Expand
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Review
2018
Review
2018
NB-CNN: Deep Learning-Based Crack Detection Using Convolutional Neural Network and Naïve Bayes Data Fusion
Regular inspection of nuclear power plant components is important to guarantee safe operations. However, current practice is time… Expand
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Review
2018
Review
2018
Deep Learning Applications in Medical Image Analysis
The tremendous success of machine learning algorithms at image recognition tasks in recent years intersects with a time of… Expand
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Review
2018
Review
2018
Quantizing deep convolutional networks for efficient inference: A whitepaper
We present an overview of techniques for quantizing convolutional neural networks for inference with integer weights and… Expand
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Review
2018
Review
2018
RGB-D-based Human Motion Recognition with Deep Learning: A Survey
Human motion recognition is one of the most important branches of human-centered research activities. In recent years, motion… Expand
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Review
2018
Review
2018
Visual interpretability for deep learning: a survey
This paper reviews recent studies in understanding neural-network representations and learning neural networks with interpretable… Expand
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Review
2018
Review
2018
Deep Learning for IoT Big Data and Streaming Analytics: A Survey
In the era of the Internet of Things (IoT), an enormous amount of sensing devices collect and/or generate various sensory data… Expand
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Review
2018
Review
2018
Recent advances in efficient computation of deep convolutional neural networks
Deep neural networks have evolved remarkably over the past few years and they are currently the fundamental tools of many… Expand
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Review
2018
Review
2018
Deep visual tracking: Review and experimental comparison
Abstract Recently, deep learning has achieved great success in visual tracking. The goal of this paper is to review the state-of… Expand
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Review
2018
Review
2018
Toolflows for Mapping Convolutional Neural Networks on FPGAs: A Survey and Future Directions
In the past decade, Convolutional Neural Networks (CNNs) have demonstrated state-of-the-art performance in various Artificial… Expand
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