Lightweight network based features fusion for steel rolling ambient sound classification-Reference-Cited by-同舟云学术

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Lightweight network based features fusion for steel rolling ambient sound classification

Published:2024-07 Issue: Volume:133 Page:108382
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Shi Rui,Zhang Fei^ORCID,Li YanJiao

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Ministry of Science and Technology of the People's Republic of China

Guangxi Key Research and Development Program

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference48 articles.

1. Explainable automated anuran sound classification using improved one-dimensional local binary pattern and Tunable Q Wavelet Transform techniques;Akbal;Expert Syst. Appl.,2023

2. FusedTSNet: an automated nocturnal sleep sound classification method based on a fused textural and statistical feature generation network;Akbal;Appl. Acoust.,2021

3. Multi-feature fusion and improved BO and IGWO metaheuristics based models for automatically diagnosing the sleep disorders from sleep sounds;Akyol;Comput. Biol. Med.,2023

4. SoundNet: Learning Sound Representations from Unlabeled Video;Aytar,2016

5. Convergence and Dynamical Behavior of the ADAM Algorithm for Nonconvex Stochastic Optimization;Barakat,2021

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