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自学教程：who is the best in CIFAR-10 ?
51自学网 2020-12-05 21:21:44
  深度学习
这篇教程who is the best in CIFAR-10 ?写得很实用，希望能帮到您。

CIFAR-10
who is the best in CIFAR-10 ?

CIFAR-10 49 results collected

Units: accuracy %

Classify 32x32 colour images.

Result Method Venue Details
96.53% Fractional Max-Pooling arXiv 2015 Details
95.59% Striving for Simplicity: The All Convolutional Net ICLR 2015 Details
94.16% All you need is a good init ICLR 2016 Details
94% Lessons learned from manually classifying CIFAR-10 unpublished 2011 Details
93.95% Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree AISTATS 2016 Details
93.72% Spatially-sparse convolutional neural networks arXiv 2014  
93.63% Scalable Bayesian Optimization Using Deep Neural Networks ICML 2015  
93.57% Deep Residual Learning for Image Recognition arXiv 2015 Details
93.45% Fast and Accurate Deep Network Learning by Exponential Linear Units arXiv 2015 Details
93.34% Universum Prescription: Regularization using Unlabeled Data arXiv 2015  
93.25% Batch-normalized Maxout Network in Network arXiv 2015 Details
93.13% Competitive Multi-scale Convolution arXiv 2015  
92.91% Recurrent Convolutional Neural Network for Object Recognition CVPR 2015 Details
92.49% Learning Activation Functions to Improve Deep Neural Networks ICLR 2015 Details
92.45% cifar.torch unpublished 2015 Details
92.40% Training Very Deep Networks NIPS 2015 Details
92.23% Stacked What-Where Auto-encoders arXiv 2015  
91.88% Multi-Loss Regularized Deep Neural Network CSVT 2015 Details
91.78% Deeply-Supervised Nets arXiv 2014 Details
91.73% BinaryConnect: Training Deep Neural Networks with binary weights during propagations NIPS 2015 Details
91.48% On the Importance of Normalisation Layers in Deep Learning with Piecewise Linear Activation Units arXiv 2015  
91.40% Spectral Representations for Convolutional Neural Networks NIPS 2015  
91.2% Network In Network ICLR 2014 Details
91.19% Speeding up Automatic Hyperparameter Optimization of Deep Neural Networks by Extrapolation of Learning Curves IJCAI 2015 Details
90.78% Deep Networks with Internal Selective Attention through Feedback Connections NIPS 2014 Details
90.68% Regularization of Neural Networks using DropConnect ICML 2013  
90.65% Maxout Networks ICML 2013 Details
90.61% Improving Deep Neural Networks with Probabilistic Maxout Units ICLR 2014 Details
90.5% Practical Bayesian Optimization of Machine Learning Algorithms NIPS 2012 Details
89.67% APAC: Augmented PAttern Classification with Neural Networks arXiv 2015  
89.14% Deep Convolutional Neural Networks as Generic Feature Extractors IJCNN 2015 Details
89% ImageNet Classification with Deep Convolutional Neural Networks NIPS 2012 Details
88.80% Empirical Evaluation of Rectified Activations in Convolution Network ICML workshop 2015 Details
88.79% Multi-Column Deep Neural Networks for Image Classification CVPR 2012 Details
87.65% ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks arXiv 2015  
86.70 % An Analysis of Unsupervised Pre-training in Light of Recent Advances ICLR 2015 Details
84.87% Stochastic Pooling for Regularization of Deep Convolutional Neural Networks arXiv 2013  
84.4% Improving neural networks by preventing co-adaptation of feature detectors arXiv 2012 Details
83.96% Discriminative Learning of Sum-Product Networks NIPS 2012  
82.9% Stable and Efficient Representation Learning with Nonnegativity Constraints ICML 2014 Details
82.2% Learning Invariant Representations with Local Transformations ICML 2012 Details
82.18% Convolutional Kernel Networks arXiv 2014 Details
82% Discriminative Unsupervised Feature Learning with Convolutional Neural Networks NIPS 2014 Details
80.02% Learning Smooth Pooling Regions for Visual Recognition BMVC 2013  
80% Object Recognition with Hierarchical Kernel Descriptors CVPR 2011  
79.7% Learning with Recursive Perceptual Representations NIPS 2012 Details
79.6 % An Analysis of Single-Layer Networks in Unsupervised Feature Learning AISTATS 2011 Details
78.67% PCANet: A Simple Deep Learning Baseline for Image Classification? arXiv 2014 Details
75.86% Enhanced Image Classification With a Fast-Learning Shallow Convolutional Neural Network arXiv 2015 Details
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