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YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry

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Published in:High Voltage
Format: Online Article RSS Article
Published: 2026
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container_title High Voltage
description
discipline_display Environmental Sciences
discipline_facet Environmental Sciences
format Online Article
RSS Article
genre Journal Article
id rss_article:30490
institution FRELIP
journal_source_facet High Voltage
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
— — — — — Energy
Environmental Management
Environmental Sciences
sub_discipline_display Environmental Management
sub_discipline_facet Environmental Management
subject_display — — — — — Energy
Environmental Management
Environmental Sciences
— — — — — Energy
Environmental Management
Environmental Sciences
subject_facet — — — — — Energy
Environmental Management
Environmental Sciences
title YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_auth YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_full YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_fullStr YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_full_unstemmed YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_short YOLO‐GDCNN: Real‐Time Operating Point Detection for Live Working Robots in the Power Industry
title_sort yolo‐gdcnn: real‐time operating point detection for live working robots in the power industry
topic — — — — — Energy
Environmental Management
Environmental Sciences
url https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/hve2.70113?af=R