A new deep learning based end-to-end pipeline for hamstring injury detection in thermal images of professional football player

IF 3.7 3区 工程技术 Q1 INSTRUMENTS & INSTRUMENTATION Quantitative Infrared Thermography Journal Pub Date : 2024-07-05 DOI:10.1080/17686733.2024.2364964
Mehmet Celalettin Ergene, Ahmet Bayrak, Murat Ceylan
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基于深度学习的新型端到端管道,用于检测职业足球运动员热图像中的腿筋损伤情况
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来源期刊
Quantitative Infrared Thermography Journal
Quantitative Infrared Thermography Journal Physics and Astronomy-Instrumentation
CiteScore
6.80
自引率
12.00%
发文量
17
审稿时长
>12 weeks
期刊介绍: The Quantitative InfraRed Thermography Journal (QIRT) provides a forum for industry and academia to discuss the latest developments of instrumentation, theoretical and experimental practices, data reduction, and image processing related to infrared thermography.
期刊最新文献
Automatic segmentation of microporous defects in composite film materials based on the improved attention U-Net module A deep learning based experimental framework for automatic staging of pressure ulcers from thermal images Two-dimensional Hilbert-Huang transform-based thermographic data processing for non-destructive material defect detection A new deep learning based end-to-end pipeline for hamstring injury detection in thermal images of professional football player Indirect thermographic die temperature measurement of a SiC-based semiconductor diode under the conditions of natural and forced convection
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