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» Learning Visual Attributes
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129
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ICDAR
2003
IEEE
15 years 8 months ago
Best Practices for Convolutional Neural Networks Applied to Visual Document Analysis
Neural networks are a powerful technology for classification of visual inputs arising from documents. However, there is a confusing plethora of different neural network methods th...
Patrice Simard, David Steinkraus, John C. Platt
113
Voted
CGF
2010
155views more  CGF 2010»
15 years 2 months ago
SmallWorlds: Visualizing Social Recommendations
We present SmallWorlds, a visual interactive graph-based interface that allows users to specify, refine and build item-preference profiles in a variety of domains. The interface f...
Brynjar Gretarsson, John O'Donovan, Svetlin Bostan...
125
Voted
CG
2007
Springer
15 years 2 months ago
Visualizing and animating the winged-edge data structure
The winged- and half- edge data structures are commonly used representations for polyhedron models. Due to the complexity, students in an introductory to computer graphics course ...
Bryan Neperud, John L. Lowther, Ching-Kuang Shene
175
Voted
CVPR
2012
IEEE
13 years 5 months ago
Boosting bottom-up and top-down visual features for saliency estimation
Despite significant recent progress, the best available visual saliency models still lag behind human performance in predicting eye fixations in free-viewing of natural scenes. ...
Ali Borji
146
Voted
ICPR
2008
IEEE
16 years 4 months ago
Joint visual vocabulary for animal classification
This paper presents a method for visual object categorization based on encoding the joint textural information in objects and the surrounding background, and requiring no segmenta...
Alireza Tavakoli Targhi, Andrzej Pronobis, Heydar ...