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» Learning Mid-Level Features For Recognition
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162
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IROS
2007
IEEE
134views Robotics» more  IROS 2007»
16 years 20 days ago
Feature selection for grasp recognition from optical markers
Abstract— Although the human hand is a complex biomechanical system, only a small set of features may be necessary for observation learning of functional grasp classes. We explor...
Lillian Y. Chang, Nancy S. Pollard, Tom M. Mitchel...
195
Voted
ICML
2010
IEEE
15 years 7 months ago
A Theoretical Analysis of Feature Pooling in Visual Recognition
Many modern visual recognition algorithms incorporate a step of spatial `pooling', where the outputs of several nearby feature detectors are combined into a local or global `...
Y-Lan Boureau, Jean Ponce, Yann LeCun
ICDAR
2003
IEEE
15 years 11 months ago
A Flexible Recognition Engine for Complex On-line Handwritten Character Recognition
A major feature of new mobiles terminals using penbased interfaces, such as personal assistants or e-book, is their personal character, implying that a good interface should be ea...
Sanparith Marukatat, Rudy Sicard, Thierry Arti&egr...
153
Voted
EMNLP
2009
15 years 4 months ago
Semi-supervised Speech Act Recognition in Emails and Forums
In this paper, we present a semi-supervised method for automatic speech act recognition in email and forums. The major challenge of this task is due to lack of labeled data in the...
Minwoo Jeong, Chin-Yew Lin, Gary Geunbae Lee
HCI
2009
15 years 4 months ago
Sign Language Recognition: Working with Limited Corpora
The availability of video format sign language corpora limited. This leads to a desire for techniques which do not rely on large, fully-labelled datasets. This paper covers various...
Helen Cooper, Richard Bowden