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» Support Vector Machines for 3D Object Recognition
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119
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AVBPA
2005
Springer
226views Biometrics» more  AVBPA 2005»
15 years 6 months ago
Discriminant Analysis Based on Kernelized Decision Boundary for Face Recognition
A novel nonlinear discriminant analysis method, Kernelized Decision Boundary Analysis (KDBA), is proposed in our paper, whose Decision Boundary feature vectors are the normal vecto...
Baochang Zhang, Xilin Chen, Wen Gao
102
Voted
ACCV
2007
Springer
15 years 7 months ago
Gesture Recognition Under Small Sample Size
This paper addresses gesture recognition under small sample size, where direct use of traditional classifiers is difficult due to high dimensionality of input space. We propose a ...
Tae-Kyun Kim, Roberto Cipolla
96
Voted
NIPS
2000
15 years 2 months ago
Vicinal Risk Minimization
The Vicinal Risk Minimization principle establishes a bridge between generative models and methods derived from the Structural Risk Minimization Principle such as Support Vector M...
Olivier Chapelle, Jason Weston, Léon Bottou...
PR
2007
165views more  PR 2007»
15 years 9 days ago
A trainable feature extractor for handwritten digit recognition
This article focusses on the problems of feature extraction and the recognition of handwritten digits. A trainable feature extractor based on the LeNet5 convolutional neural netwo...
Fabien Lauer, Ching Y. Suen, Gérard Bloch
101
Voted
MLDM
2005
Springer
15 years 6 months ago
Low-Level Cursive Word Representation Based on Geometric Decomposition
Abstract. An efficient low-level word image representation plays a crucial role in general cursive word recognition. This paper proposes a novel representation scheme, where a word...
Jian-xiong Dong, Adam Krzyzak, Ching Y. Suen, Domi...