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Hitham Jleed
University of Ottawa School of Electrical Engineering and Computer Science.
Computer Science & IT

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Incremental Multiclass Open-set Audio Recognition Hitham Jleed; Martin Bouchard
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v8i2.812

Abstract

Incremental learning aims to learn new classes if they emerge while maintaining the performance for previously known classes. It acquires useful information from incoming data to update the existing models. Open-set recognition, however, requires the ability to recognize examples from known classes and reject examples from new/unknown classes. In this work, we propose a combination of multiclass open-set recognition and an incremental learning scheme in the audio recognition domain. We introduce incremental open-set multiclass support vector machine algorithms that can classify examples from seen/unseen classes, using incremental learning to increase the current model with new classes without entirely retraining the system. Comprehensive evaluations carried out on problems of multi-class open-set recognition showed promising performance for the proposed methods, compared with some representative previous methods
Co-Authors Martin Bouchard