Who Cited It

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

2017 · Neural Computation · 3,570 citations · 2 from inside this corpus

Waseem Rawat low, Zenghui Wang

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review (2017)Deep Convolutional Neural Net…Long Short-Term Memory (1997)Long Short-Term MemoryAdam: A Method for Stochastic Optimization (2014)Adam: A Method for Stochastic…The Nature of Statistical Learning Theory (1995)The Nature of Statistical Lea…Dropout: a simple way to prevent neural networks from overfitting (2014)Dropout: a simple way to prev…Learning representations by back-propagating errors (1986)Learning representations by b…Reducing the Dimensionality of Data with Neural Networks (2006)Reducing the Dimensionality o…Xception: Deep Learning with Depthwise Separable Convolutions (2017)Xception: Deep Learning with …Deep learning in neural networks: An overview (2014)Deep learning in neural netwo…A Fast Learning Algorithm for Deep Belief Nets (2006)A Fast Learning Algorithm for…Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh… (2024)Batch Normalization: Accelera…Advances in Neural Information Processing Systems 19 (2007)Advances in Neural Informatio…A new optimizer using particle swarm theory (2002)A new optimizer using particl…Advances in Neural Information Processing Systems 28 (2015)Advances in Neural Informatio…Distilling the Knowledge in a Neural Network (2015)Distilling the Knowledge in a…Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning (2017)Inception-v4, Inception-ResNe…Understanding the difficulty of training deep feedforward neural networks (2010)Understanding the difficulty …Aggregated Residual Transformations for Deep Neural Networks (2017)Aggregated Residual Transform…Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …Learning long-term dependencies with gradient descent is difficult (1994)Learning long-term dependenci…Domain-Adversarial Training of Neural Networks (2017)Domain-Adversarial Training o…Learning Deep Architectures for AI (2009)Learning Deep Architectures f…Improving neural networks by preventing co-adaptation of feature detectors (2012)Improving neural networks by …Proceedings of the 19th International Joint Conference on Artificial Intelligence (2005)Proceedings of the 19th Inter…Large-Scale Machine Learning with Stochastic Gradient Descent (2010)Large-Scale Machine Learning …ADADELTA: An Adaptive Learning Rate Method (2012)ADADELTA: An Adaptive Learnin…Deep Sparse Rectifier Neural Networks (2011)Deep Sparse Rectifier Neural …Learning Deep Architectures for AI (2009)Training Products of Experts by Minimizing Contrastive Divergence (2002)Training Products of Experts …On the importance of initialization and momentum in deep learning (2013)On the importance of initiali…Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex… (2006)Manifold Regularization: A Ge…One-shot learning of object categories (2006)One-shot learning of object c…Convergence Results for Neural Networks via Electrodynamics (2018)Convergence Results for Neura…Advances in Neural Information Processing Systems 37 (2024)Advances in Neural Informatio…Proceedings of the International Joint Conference on Artificial Intelligence 2007 (2007)Proceedings of the Internatio…A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures (2019)A Review of Recurrent Neural …A State-of-the-Art Survey on Deep Learning Theory and Architectures (2019)A State-of-the-Art Survey on …
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What this paper cites, inside the corpus

PaperYearCited
Long Short-Term Memory1997101,359
Adam: A Method for Stochastic Optimization201484,698
The Nature of Statistical Learning Theory199539,409
Dropout: a simple way to prevent neural networks from overfitting201434,236
Learning representations by back-propagating errors198631,688
Reducing the Dimensionality of Data with Neural Networks200621,247
Xception: Deep Learning with Depthwise Separable Convolutions201719,457
Deep learning in neural networks: An overview201418,236
A Fast Learning Algorithm for Deep Belief Nets200616,540
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…202415,663
Advances in Neural Information Processing Systems 19200715,653
A new optimizer using particle swarm theory200214,967
Advances in Neural Information Processing Systems 28201514,672
Distilling the Knowledge in a Neural Network201514,099
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning201712,734
Understanding the difficulty of training deep feedforward neural networks201012,673
Aggregated Residual Transformations for Deep Neural Networks201712,015
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization20108,621
Learning long-term dependencies with gradient descent is difficult19948,610
Domain-Adversarial Training of Neural Networks20177,702
Learning Deep Architectures for AI20096,951
Improving neural networks by preventing co-adaptation of feature detectors20126,653
Proceedings of the 19th International Joint Conference on Artificial Intelligence20055,782
Large-Scale Machine Learning with Stochastic Gradient Descent20105,695
ADADELTA: An Adaptive Learning Rate Method20125,532
Deep Sparse Rectifier Neural Networks20115,428
Learning Deep Architectures for AI20095,077
Training Products of Experts by Minimizing Contrastive Divergence20025,032
On the importance of initialization and momentum in deep learning20133,523
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex…20063,266
One-shot learning of object categories20063,095
Convergence Results for Neural Networks via Electrodynamics20182,943
Advances in Neural Information Processing Systems 3720242,802
Proceedings of the International Joint Conference on Artificial Intelligence 200720072,765

What cites it, inside the corpus

PaperYearCited
A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures20195,628
A State-of-the-Art Survey on Deep Learning Theory and Architectures20191,619

Links

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Topics

Domain Adaptation and Few-Shot LearningComputer Science
Advanced Neural Network ApplicationsComputer Science
Advanced Image and Video Retrieval TechniquesComputer Science

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complete

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  • supports2 author record(s) attached.
  • supports289 reference(s) recorded.
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  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:46+00:00.

sha256 bba2969b3567609a…