Results shown indicates the error obtained by training on all 60,000 samples and testing on 10,000 samples.

- Multi-column Deep Neural Networks for Image Classiﬁcation (CVPR 2012)

Cited 9 times.**0.23%**

Supplemental material, Technical Report - Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition (2010)

Cited 1 time.**0.35%**

Additional info: 6-layer NN 784-2500-2000-1500-1000-500-10 (on GPU) [elastic distortions] - Efﬁcient Learning of Sparse Representations with an Energy-Based Model (2006)

Cited 109 times.**0.39%**

Additional info: large conv. net, unsup pretraining [elastic distortions] - Stochastic Pooling for Regularization of Deep Convolutional Neural Networks (2013)

Cited 1 times.**0.47%**

Additional info: Stochastic Pooling - Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis (2003)

Cited 190 times.**0.4%** - What is the Best Multi-Stage Architecture for Object Recognition? (ICCV 2009)

Cited 39 times.**0.53%**

Additional info: large conv. net, unsup pretraining [no distortions] - Deformation Models for Image Recognition (PAMI 2007)

Cited 46 times.**0.54%**

Additional info: K-NN with non-linear deformation (IDM) (Preprocessing: shiftable edges) - A trainable feature extractor for handwritten digit recognition (2007)

Cited 38 times.**0.54%**

Additional info: Trainable feature extractor + SVMs [affine distortions] - Training Invariant Support Vector Machines (2002)

Cited 281 times.**0.56%**

Additional info: Virtual SVM, deg-9 poly, 2-pixel jittered (Preprocessing: deskewing) - Simple Methods for High-Performance Digit Recognition Based on Sparse Coding (TNN 2008)

0.59%

Additional info: unsupervised sparse features + SVM, [no distortions] - Unsupervised learning of invariant feature hierarchies with applications to object recognition (CVPR 2007)

Cited 119 times.**0.62%**

Additional info: large conv. net, unsup features [no distortions] - Shape matching and object recognition using shape contexts (PAMI 2002)

Cited 2089 times.**0.63%**

Additional info: K-NN, shape context matching (preprocessing: shape context feature extraction) - Beyond Spatial Pyramids: Receptive Field Learning for Pooled Image Features (2012)

Cited 0 times.**0.64%** - Convolutional Deep Belief Networks for Scalable Unsupervised Learning of Hierarchical Representations (2009)

0.82% - Large-Margin kNN Classification using a Deep Encoder Network (2009)

0.94%

- Deep Boltzmann Machines (2009)

0.95% - CS81: Learning words with Deep Belief Networks (2008)

1.12% - Convolutional Neural Networks (2003)

1.19%

More info: The ConvNN is based on the paper "Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis".

- Reducing the dimensionality of data with neural networks (2006)

1.2% - Deep learning via semi-supervised embedding (2008)

1.5%