Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Combination of multiple classifiers for the customer's purchase behavior prediction
Decision Support Systems - Special issue: Agents and e-commerce business models
Chirplet Transform Applied to Simulated and Real Blue Whale (Balaenoptera musculus) Calls
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Financial distress prediction based on serial combination of multiple classifiers
Expert Systems with Applications: An International Journal
Computers in Biology and Medicine
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
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In this paper, we propose a serial combination architecture of classifiers for automatic blue whale calls recognition. Based on class's best selection operator, the proposed system uses a best classifier for D call class followed by another one that efficiently discriminate the A and B calls. The first classifier uses the short-time Fourier transform to characterize the patterns, while the second uses the chirplet transform. Both classifiers are based on multi-layer perceptron neural network. The classification performance (95.55%) of the proposed system outperforms all tested single classifiers. The other advantages of the system are no requirement for adjusting a series of parameters and simple feature extraction.