User contributions for X435liu

5 December 2015

• 18:3518:35, 5 December 2015 diff hist +357‎ very Deep Convoloutional Networks for Large-Scale Image Recognition ‎ →‎Conv.Net Configurations
• 18:2518:25, 5 December 2015 diff hist 0‎ m very Deep Convoloutional Networks for Large-Scale Image Recognition ‎ →‎Conclusion
• 17:0717:07, 5 December 2015 diff hist +297‎ deep Sparse Rectifier Neural Networks ‎ →‎Results
• 17:0117:01, 5 December 2015 diff hist +570‎ deep Sparse Rectifier Neural Networks ‎No edit summary
• 16:4816:48, 5 December 2015 diff hist −2‎ m deep Sparse Rectifier Neural Networks ‎No edit summary
• 16:4816:48, 5 December 2015 diff hist +35‎ m deep Sparse Rectifier Neural Networks ‎No edit summary
• 16:4716:47, 5 December 2015 diff hist +304‎ deep Sparse Rectifier Neural Networks ‎ →‎Biological Plausibility and Sparsity
• 16:3416:34, 5 December 2015 diff hist +342‎ deep Sparse Rectifier Neural Networks ‎ →‎Introduction

17 November 2015

• 22:0422:04, 17 November 2015 diff hist +275‎ dropout ‎ →‎Result
• 21:5521:55, 17 November 2015 diff hist +354‎ dropout ‎ →‎Result
• 21:5521:55, 17 November 2015 diff hist 0‎ N File:Dropout.PNG ‎No edit summary current
• 21:4821:48, 17 November 2015 diff hist −1‎ m dropout ‎ →‎Effects of Dropout
• 21:4721:47, 17 November 2015 diff hist +276‎ dropout ‎ →‎Effects of Dropout
• 17:4317:43, 17 November 2015 diff hist +451‎ dropout ‎ →‎Model

13 November 2015

• 21:4821:48, 13 November 2015 diff hist +35‎ m joint training of a convolutional network and a graphical model for human pose estimation ‎No edit summary
• 21:4521:45, 13 November 2015 diff hist +2‎ m joint training of a convolutional network and a graphical model for human pose estimation ‎ →‎Higher-Level Spatial-Model
• 21:4321:43, 13 November 2015 diff hist +1,000‎ joint training of a convolutional network and a graphical model for human pose estimation ‎ →‎Results
• 21:4221:42, 13 November 2015 diff hist 0‎ N File:Result2.PNG ‎No edit summary current
• 21:3721:37, 13 November 2015 diff hist 0‎ N File:Result1.PNG ‎No edit summary current
• 21:3321:33, 13 November 2015 diff hist +277‎ joint training of a convolutional network and a graphical model for human pose estimation ‎ →‎Unified Model
• 21:3321:33, 13 November 2015 diff hist +2,743‎ joint training of a convolutional network and a graphical model for human pose estimation ‎ →‎Higher-Level Spatial-Model
• 21:2921:29, 13 November 2015 diff hist 0‎ N File:Architecture2.PNG ‎No edit summary current
• 21:0921:09, 13 November 2015 diff hist +1,655‎ joint training of a convolutional network and a graphical model for human pose estimation ‎ →‎Convolutional Network Part-Detector
• 21:0021:00, 13 November 2015 diff hist 0‎ N File:Architecture1.PNG ‎No edit summary current
• 20:5820:58, 13 November 2015 diff hist +1,199‎ N joint training of a convolutional network and a graphical model for human pose estimation ‎ Created page with "== Introduction == Human body pose estimation, or specifically the localization of human joints in monocular RGB images, remains a very challenging task in computer vision. Rece..."
• 20:5320:53, 13 November 2015 diff hist +3‎ f15Stat946PaperSignUp ‎ →‎Set B

11 November 2015

• 15:4415:44, 11 November 2015 diff hist −34‎ m imageNet Classification with Deep Convolutional Neural Networks ‎ →‎Overall Architecture
• 15:4315:43, 11 November 2015 diff hist 0‎ File:Network.JPG ‎ uploaded a new version of "File:Network.JPG" current
• 15:3815:38, 11 November 2015 diff hist +5,345‎ imageNet Classification with Deep Convolutional Neural Networks ‎No edit summary
• 15:2315:23, 11 November 2015 diff hist 0‎ N File:Network.JPG ‎No edit summary
• 15:0115:01, 11 November 2015 diff hist +416‎ imageNet Classification with Deep Convolutional Neural Networks ‎ →‎Dataset
• 15:0015:00, 11 November 2015 diff hist +37‎ imageNet Classification with Deep Convolutional Neural Networks ‎No edit summary
• 14:5914:59, 11 November 2015 diff hist +78‎ m imageNet Classification with Deep Convolutional Neural Networks ‎ →‎Introduction
• 14:5614:56, 11 November 2015 diff hist +824‎ imageNet Classification with Deep Convolutional Neural Networks ‎ →‎Introduction
• 14:5214:52, 11 November 2015 diff hist +152‎ N imageNet Classification with Deep Convolutional Neural Networks ‎ Created page with "== Introduction == == Dataset == == Architecture == == Reducing overfitting == == Details of leaning == == Results == == Discussion =="

8 November 2015

• 17:1717:17, 8 November 2015 diff hist +353‎ f15Stat946PaperSignUp ‎ →‎Set B

2 November 2015

• 20:1020:10, 2 November 2015 diff hist +128‎ m learning Hierarchical Features for Scene Labeling ‎ →‎Network Architecture
• 20:0120:01, 2 November 2015 diff hist +248‎ learning Hierarchical Features for Scene Labeling ‎ →‎Network Architecture
• 19:5019:50, 2 November 2015 diff hist +356‎ learning Hierarchical Features for Scene Labeling ‎ →‎Network Architecture
• 19:2819:28, 2 November 2015 diff hist 0‎ learning Hierarchical Features for Scene Labeling ‎ →‎Methodology
• 19:2419:24, 2 November 2015 diff hist +330‎ learning Hierarchical Features for Scene Labeling ‎ →‎Introduction
• 16:1316:13, 2 November 2015 diff hist +340‎ human-level control through deep reinforcement learning ‎ →‎The Full Algorithm
• 15:3815:38, 2 November 2015 diff hist +811‎ human-level control through deep reinforcement learning ‎ →‎Overcoming Instability

28 October 2015

• 23:1623:16, 28 October 2015 diff hist +28‎ overfeat: integrated recognition, localization and detection using convolutional networks ‎ →‎Multi-Scale Classification
• 23:1123:11, 28 October 2015 diff hist +1,192‎ overfeat: integrated recognition, localization and detection using convolutional networks ‎ →‎Classification
• 22:3722:37, 28 October 2015 diff hist +133‎ overfeat: integrated recognition, localization and detection using convolutional networks ‎ →‎Introduction

21 October 2015

• 23:0223:02, 21 October 2015 diff hist +506‎ parsing natural scenes and natural language with recursive neural networks ‎No edit summary
• 22:3622:36, 21 October 2015 diff hist +145‎ parsing natural scenes and natural language with recursive neural networks ‎ →‎Scene understanding
• 21:2621:26, 21 October 2015 diff hist +381‎ parsing natural scenes and natural language with recursive neural networks ‎ →‎Learning
• 21:0621:06, 21 October 2015 diff hist +362‎ parsing natural scenes and natural language with recursive neural networks ‎ →‎Introduction