Independent component analysis: algorithms and applications
Neural Networks
Iris Image Denoising Algorithm Based on Phase Preserving
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Study on Classification Method Based on Support Vector Machine
ETCS '09 Proceedings of the 2009 First International Workshop on Education Technology and Computer Science - Volume 02
Fast kernel-based independent component analysis
IEEE Transactions on Signal Processing
Independent component analysis-based background subtraction for indoor surveillance
IEEE Transactions on Image Processing
Face recognition by independent component analysis
IEEE Transactions on Neural Networks
Support vector machine for breast MR image classification
Computers & Mathematics with Applications
Computers & Mathematics with Applications
Automatic recognition of frog calls using a multi-stage average spectrum
Computers & Mathematics with Applications
Fast pedestrian detection system with a two layer cascade of classifiers
Computers & Mathematics with Applications
A nonparametric-based rib suppression method for chest radiographs
Computers & Mathematics with Applications
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Imbalance of gender ratio at birth has been a serious phenomenon in China. To solve this problem, a scheme for ultrasonic image classification is proposed for preventing fetus gender examination with non-medical purposes. Tens of thousands of ultrasonic images with and without sexual organs are collected to establish a professional database. These images are preprocessed firstly by cropping, de-noising and compression. And then, independent component analysis (ICA) is applied for feature extraction under two architectures, which give local and global information respectively. The first architecture treats the images as random variables and the pixels as outcomes, while the second treats the pixels as random variables and the images as outcomes. After training of selected samples, a support vector machine (SVM) classifier which combined the two ICA representations is established for recognition, and a good performance is given for testing data. Finally, some new technique is suggested for algorithm improvement in the future.