Machine learning-based classification of bronze alloy cymbals from microphone captured data enhanced with feature selection approaches-Reference-Cited by-同舟云学术

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Machine learning-based classification of bronze alloy cymbals from microphone captured data enhanced with feature selection approaches

Published:2023-04 Issue: Volume:215 Page:119378
ISSN:0957-4174
Container-title:Expert Systems with Applications
language:en
Short-container-title:Expert Systems with Applications

Author:

Boratto Tales H.A.^ORCID,Cury Alexandre A.^ORCID,Goliatt Leonardo^ORCID

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Fundação de Amparo à Pesquisa do Estado de Minas Gerais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference39 articles.

1. Relationship between chaotic vibrations and acoustic properties of percussion cymbals;Aihara;Results in Engineering,2022

2. C414 XLII - Reference multipattern condenser microphone;AKG,2021

3. TSFEL: Time series feature extraction library;Barandas;SoftwareX,2020

4. Crash cymbal sounds;Boratto,2022

5. A fuzzy approach to drum cymbals classification;Boratto;IEEE Latin America Transactions,2022

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1. Hybridized machine learning models for phosphate pollution modeling in water systems for multiple uses;Journal of Water Process Engineering;2024-07

2. Audio Recognition of the Percussion Sounds Generated by a 3D Auto-Drum Machine System via Machine Learning;Electronics;2024-05-06

3. Research in the Department of Music Technology and Acoustics of the Hellenic Mediterranean University: An Overview and Prospects;WSEAS TRANSACTIONS ON ACOUSTICS AND MUSIC;2024-03-20

4. Development of hybrid computational data-intelligence model for flowing bottom-hole pressure of oil wells: New strategy for oil reservoir management and monitoring;Fuel;2023-10

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