A Comparative Analysis of Residual Block Alternatives for End-to-End Audio Classification
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DOI: 10.1109/access.2020.3031685
Abstract: Residual learning is known for being a learning framework that facilitates the training of very deep neural networks. Residual blocks or units are made up of a set of stacked layers, where the inputs are… read more here.
Keywords: residual block; block; end end; audio classification ... See more keywords
Pruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-Devices
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DOI: 10.1109/access.2022.3140807
Abstract: Deep learning has celebrated resounding successes in many application areas of relevance to the Internet of Things (IoT), such as computer vision and machine listening. These technologies must ultimately be brought directly to the edge… read more here.
Keywords: study; xnor net; classification; deep learning ... See more keywords
Few-shot Class-incremental Audio Classification Using Dynamically Expanded Classifier with Self-attention Modified Prototypes
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Multimedia"
DOI: 10.1109/tmm.2023.3280011
Abstract: Most existing methods for audio classification assume that the vocabulary of audio classes to be classified is fixed. When novel (unseen) audio classes appear, audio classification systems need to be retrained with abundant labeled samples… read more here.
Keywords: audio classification; classifier; novel audio; audio classes ... See more keywords