Enhancing Classification Accuracy and Speed with ML-DSP: A Game-Changer in Genomic Sequence Analysis-Reference-Cited by-同舟云学术

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Enhancing Classification Accuracy and Speed with ML-DSP: A Game-Changer in Genomic Sequence Analysis

Published:2023-12-01 Issue: Volume: Page:1-6
ISSN:
Container-title:2023 IEEE 3rd Mysore Sub Section International Conference (MysuruCon)
language:
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Author:

M D Rakesh¹,R Madhura²,R Shashidhar¹,Krishnappa Krutthika Hirebasur³

Affiliation:

1. JSS Science and Trechnology University,Department of Electronics and Communication Engineering,Mysuru,India

2. Dayananda Sagar College of Engineering,Department of Electronics and Communication Engineering,Bengaluru,India

3. Southern University and A&M College,Department of Computer Science,Baton Rouge,Louisina,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10395909/10396851/10396995.pdf?arnumber=10396995

Reference18 articles.

1. ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels

2. Taxonomic Classification for Living Organisms Using Convolutional Neural Networks

3. Machine learning approach to support taxonomic species discrimination based on helminth collections data

4. Classification of Eukaryotic Organisms Through Cepstral Analysis of Mitochondrial DNA

5. Prediction of antimicrobial resistance based on whole-genome sequencing and machine learning

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