Using Convolutional Neural Networks to Measure the Physiological Age of Caenorhabditis elegans
Author:
Funder
Ministry of Science and Technology, Taiwan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Applied Mathematics,Genetics,Biotechnology
Link
http://xplorestaging.ieee.org/ielx7/8857/9642421/08985285.pdf?arnumber=8985285
Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
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2. A Comparative Analysis on Detecting Physiological Age of Caenorhabditis Elegans Using Deep Learning Techniques;2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI);2023-12-09
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4. Automation of Caenorhabditis elegans lifespan assay using a simplified domain synthetic image-based neural network training strategy;Computational and Structural Biotechnology Journal;2023
5. Convolutional Neural Networks for C. Elegans Muscle Age Classification Using Only Self-learned Features;Journal of Telecommunications and Information Technology;2022-12-29
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