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Neural Network Simulation

Known as: Neural Networks (Computer), Network, Neural (Computer), Perceptrons 
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which… 
National Institutes of Health

Related topics

Related topics

2 relations
Artificial Intelligencecomputational neuroscience

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2020
Highly Cited
2020
Focal Loss for Dense Object Detection
The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is… 
Highly Cited
2018
Highly Cited
2018
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
In this work we address the task of semantic image segmentation with Deep Learning and make three main contributions that are… 
Highly Cited
2017
Highly Cited
2017
Dermatologist-level classification of skin cancer with deep neural networks
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and… 
Highly Cited
2016
Highly Cited
2016
Mastering the game of Go with deep neural networks and tree search
The game of Go has long been viewed as the most challenging of classic games for artificial intelligence owing to its enormous… 
Highly Cited
2015
Highly Cited
2015
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like… 
Review
2015
Review
2015
Deep Learning
Machine-learning technology powers many aspects of modern society: from web searches to content filtering on social networks to… 
Highly Cited
2007
Highly Cited
2007
Classification and Regression by randomForest
Recently there has been a lot of interest in “ensemble learning” — methods that generate many classifiers and aggregate their… 
Highly Cited
2006
Highly Cited
2006
Reducing the Dimensionality of Data with Neural Networks
High-dimensional data can be converted to low-dimensional codes by training a multilayer neural network with a small central… 
Review
1998
Review
1998
Gradient-based learning applied to document recognition
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based… 
Highly Cited
1990
Highly Cited
1990
Identification and control of dynamical systems using neural networks
It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems… 
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