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» Learning Mid-Level Features For Recognition
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ICDAR
2003
IEEE
14 years 27 days ago
Mirror Image Learning for Autoassociative Neural Networks
This paper studies on the mirror image learning algorithm for the autoassociative neural networks and evaluates the performance by handwritten numeral recognition test. Each of th...
Shusaku Shimizu, Wataru Ohyama, Tetsushi Wakabayas...
AAAI
2000
13 years 9 months ago
Self-Supervised Learning for Visual Tracking and Recognition of Human Hand
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
Ying Wu, Thomas S. Huang
MVA
1996
167views Computer Vision» more  MVA 1996»
13 years 9 months ago
Applying a Dynamic Recognition Scheme for Vehicle Recognition in Many Object Traffic Scenes
An adaptive object recognition scheme for image sequences of many object scenes is described. The scheme is applied for t r d c object recognition under ego-motion. The recursive ...
Wlodzimierz Kasprzak, Heinrich Niemann
ICTAI
1993
IEEE
13 years 11 months ago
Robust Feature Selection Algorithms
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
Haleh Vafaie, Kenneth DeJong
ICMCS
2007
IEEE
214views Multimedia» more  ICMCS 2007»
14 years 1 months ago
Exploring Discriminative Learning for Text-Independent Speaker Recognition
Speaker verification is a technology of verifying the claimed identity of a speaker based on the speech signal from the speaker (voice print). To learn the score of similarity be...
Ming Liu, Zhengyou Zhang, Mark Hasegawa-Johnson, T...