Impact Evaluation of Sound Dataset Augmentation and Synthetic Generation upon Classification Accuracy

We investigate the impact of dataset augmentation and synthetic generation techniques on the accuracy of supervised audio classification based on state-of-the-art neural networks used as classifiers. Dataset augmentation techniques are applied upon the raw sound and its transformed image format. Spe...

詳細記述

書誌詳細

出版年:	Journal of Sensor and Actuator Networks
主要な著者:	Eleni Tsalera, Andreas Papadakis, Gerasimos Pagiatakis, Maria Samarakou
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-09-01
主題:	dataset enhancement wavelet manipulation scalogram augmentations synthetic sound generation classification accuracy
オンライン･アクセス:	https://www.mdpi.com/2224-2708/14/5/91