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» Robust classification for skewed data
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BSN
2009
IEEE
189views Sensor Networks» more  BSN 2009»
13 years 5 months ago
Neural Network Gait Classification for On-Body Inertial Sensors
Clinicians have determined that continuous ambulatory monitoring provides significant preventative and diagnostic benefit, especially to the aged population. In this paper we descr...
Mark A. Hanson, Harry C. Powell Jr., Adam T. Barth...
CVPR
2005
IEEE
14 years 9 months ago
Part-Based Statistical Models for Object Classification and Detection
We propose using simple mixture models to define a set of mid-level binary local features based on binary oriented edge input. The features capture natural local structures in the...
Elliot Joel Bernstein, Yali Amit
JMLR
2002
106views more  JMLR 2002»
13 years 7 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
PR
2008
154views more  PR 2008»
13 years 7 months ago
Data-driven decomposition for multi-class classification
This paper presents a new study on a method of designing a multi-class classifier: Data-driven Error Correcting Output Coding (DECOC). DECOC is based on the principle of Error Cor...
Jie Zhou, Hanchuan Peng, Ching Y. Suen
ICASSP
2011
IEEE
12 years 11 months ago
Using residual vector quantization for image content classification
Multistage residual vector quantizers (RVQ) with optimal direct sum decoder codebooks have been successfully designed and implemented for data compression. Due to its multistage s...
Syed Irteza Ali Khan, Christopher F. Barnes