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ImageNet
Results: 54

#	Item
21	The Cityscapes Dataset for Semantic Urban Scene Understanding Marius Cordts1,2 Mohamed Omran3 Sebastian Ramos1,4 Timo Rehfeld1,2 Markus Enzweiler1 Add to Reading List Source URL: dl.dropboxusercontent.com Language: English Image processing Computer vision Image segmentation LabelMe ImageNet Annotation Deep learning Conference on Computer Vision and Pattern Recognition Convolutional neural network
22	Visual Concept Learning: Combining Machine Vision and Bayesian Generalization on Concept Hierarchies Yangqing Jia1 , Joshua Abbott2 , Joseph Austerweil3 , Thomas Griffiths2 , Trevor Darrell1 1 UC Berkeley EECS 2 Dept of Add to Reading List Source URL: cocosci.berkeley.edu Language: English - Date: 2014-02-14 18:19:32 Statistics Artificial intelligence Machine learning Cognition Computational neuroscience Concept learning Learning theory ImageNet Artificial neural network Supervised learning Support vector machine Probability distribution
23	Deep Networks Jin Sun * Some figures are from Andrew Ng’s cs294a course notes. * Some figures are from Alex Krizhevsky’s ImageNet paper. Add to Reading List Source URL: alex.smola.org Language: English
24	Optimization of Robust Loss Functions for Weakly-Labeled Image Taxonomies: An ImageNet Case Study Julian J. McAuley1 , Arnau Ramisa2 , and Tib´erio S. Caetano1 1 Add to Reading List Source URL: tiberiocaetano.com Language: English - Date: 2011-06-05 20:39:18
25	Residual Networks for Tiny ImageNet Hansohl Kim Stanford University Abstract Add to Reading List Source URL: cs231n.stanford.edu Language: English - Date: 2016-03-23 18:05:40
26	Toward a Taxonomy and Computational Models of Abnormalities in Images Ahmed Elgammal Dept. of Computer Science Rutgers University New Jersey , USA Add to Reading List Source URL: ai2-website.s3.amazonaws.com Language: English - Date: 2016-05-10 13:04:52 Abnormal psychology ImageNet Normality Abnormality Category Anomaly detection Behavior Philosophy Behavioural sciences
27	Objects as Attributes for Scene Classification Li-Jia Li, Hao Su, Yongwhan Lim, Li Fei-Fei Computer Science Department, Stanford University Abstract. Robust low-level image features have proven to be effective represen Add to Reading List Source URL: vision.stanford.edu Language: English - Date: 2010-07-14 19:17:56 Computer vision Artificial intelligence Vision ImageNet Outline of object recognition LabelMe One-shot learning Cognitive neuroscience of visual object recognition
28	Best of both worlds: human-machine collaboration for object annotation Olga Russakovsky1 Li-Jia Li2 Li Fei-Fei1 1 Stanford University 2 Snapchat∗ Abstract Add to Reading List Source URL: ai.stanford.edu Language: English - Date: 2015-04-12 19:52:49 Machine learning Image segmentation ImageNet Conference on Computer Vision and Pattern Recognition Automatic image annotation Minimum bounding box Pattern recognition Object detection Computer vision
29	Fine-Grained Recognition without Part Annotations Jonathan Krause1 Hailin Jin2 1 Stanford University Add to Reading List Source URL: vision.stanford.edu Language: English - Date: 2015-07-12 18:35:39 IEEE conferences Image segmentation Image processing Conference on Computer Vision and Pattern Recognition GrabCut ImageNet Computer vision International Conference on Computer Vision British Machine Vision Conference Outline of object recognition Minimum bounding box
30	From Image-level to Pixel-level Labeling with Convolutional Networks Pedro O. Pinheiro1,2 Ronan Collobert1,3,† 1 Idiap Research Institute, Martigny, Switzerland 2 Add to Reading List Source URL: ronan.collobert.com Language: English - Date: 2015-08-30 20:06:35 Artificial intelligence Computer vision Vision Image processing Image segmentation Convolutional neural network ImageNet Conference on Computer Vision and Pattern Recognition Mixture model Deep learning

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