暂无分享,去创建一个
Peter Kontschieder | Antonio Criminisi | Jamie Shotton | Matthew Brown | Darko Zikic | Duncan P. Robertson | Yani Ioannou | J. Shotton | A. Criminisi | P. Kontschieder | Yani Andrew Ioannou | D. Robertson | D. Zikic | Matthew Brown
[1] Lawrence D. Jackel,et al. Handwritten Digit Recognition with a Back-Propagation Network , 1989, NIPS.
[2] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[3] Xiaogang Wang,et al. Deep Convolutional Network Cascade for Facial Point Detection , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[4] Dumitru Erhan,et al. Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Jian Sun,et al. Efficient and accurate approximations of nonlinear convolutional networks , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Dong Yu,et al. Automatic Speech Recognition: A Deep Learning Approach , 2014 .
[7] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[8] Alex Krizhevsky,et al. Learning Multiple Layers of Features from Tiny Images , 2009 .
[9] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[10] Antonio Criminisi,et al. Decision Forests for Computer Vision and Medical Image Analysis , 2013, Advances in Computer Vision and Pattern Recognition.
[11] Rich Caruana,et al. Do Deep Nets Really Need to be Deep? , 2013, NIPS.
[12] Qiang Chen,et al. Network In Network , 2013, ICLR.
[13] Trevor Darrell,et al. Caffe: Convolutional Architecture for Fast Feature Embedding , 2014, ACM Multimedia.
[14] Paul A. Viola,et al. Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.
[15] Misha Denil,et al. Predicting Parameters in Deep Learning , 2014 .
[16] Wayne Ieee,et al. Entropy Nets: From Decision Trees to Neural Networks , 1990 .
[17] Jasper Snoek,et al. Practical Bayesian Optimization of Machine Learning Algorithms , 2012, NIPS.
[18] Johannes Welbl,et al. Casting Random Forests as Artificial Neural Networks (and Profiting from It) , 2014, GCPR.
[19] Yali Amit,et al. Shape Quantization and Recognition with Randomized Trees , 1997, Neural Computation.
[20] Dimitris N. Metaxas,et al. Entangled Decision Forests and Their Application for Semantic Segmentation of CT Images , 2011, IPMI.
[21] Peter Kontschieder,et al. Deep Neural Decision Forests , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[22] Horst Bischof,et al. Alternating Decision Forests , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[23] Sebastian Nowozin,et al. Decision Jungles: Compact and Rich Models for Classification , 2013, NIPS.
[24] Alberto Suárez,et al. Globally Optimal Fuzzy Decision Trees for Classification and Regression , 1999, IEEE Trans. Pattern Anal. Mach. Intell..
[25] Peter Kontschieder,et al. Neural Decision Forests for Semantic Image Labelling , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[26] Xiang Zhang,et al. OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks , 2013, ICLR.
[27] Michael S. Bernstein,et al. ImageNet Large Scale Visual Recognition Challenge , 2014, International Journal of Computer Vision.
[28] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[29] Joan Bruna,et al. Exploiting Linear Structure Within Convolutional Networks for Efficient Evaluation , 2014, NIPS.
[30] Xiaogang Wang,et al. Multi-stage Contextual Deep Learning for Pedestrian Detection , 2013, 2013 IEEE International Conference on Computer Vision.
[31] Léon Bottou,et al. Stochastic Gradient Descent Tricks , 2012, Neural Networks: Tricks of the Trade.