{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T06:08:41Z","timestamp":1770962921678,"version":"3.50.1"},"reference-count":40,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T00:00:00Z","timestamp":1769817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["12501725"],"award-info":[{"award-number":["12501725"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Science and Technology Project in Sichuan","award":["2024YFFK0362"],"award-info":[{"award-number":["2024YFFK0362"]}]},{"name":"Science and Technology Project in Sichuan","award":["24ZYZYTS0226"],"award-info":[{"award-number":["24ZYZYTS0226"]}]},{"name":"Science and Technology Project in Sichuan","award":["2026YFHZ0219"],"award-info":[{"award-number":["2026YFHZ0219"]}]},{"name":"Sichuan Provincial Program of Traditional Chinese Medicine of China","award":["2024ZD014"],"award-info":[{"award-number":["2024ZD014"]}]},{"name":"Scientific and Technological Innovation Team for Qinghai-Tibetan Plateau Research in Southwest Minzu University","award":["2024CXTD19"],"award-info":[{"award-number":["2024CXTD19"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Power-line presence recognition technology for unmanned aerial vehicles (UAVs) is one of the key research directions in the field of UAV remote sensing. With the rapid development of UAV technology, the application of UAVs in various fields has become increasingly widespread. However, when flying in urban and rural areas, UAVs often face the danger of obstacles such as power lines, posing challenges to flight safety and stability. To address this issue, this study proposes a novel method for presence recognition in UAVs for power lines using an improved GhostNet v2 knowledge distillation dual-attention mechanism convolutional neural network. The construction of a real-time UAV power-line presence recognition system involves three aspects: dataset acquisition, a novel network model, and real-time presence recognition. First, by cleaning, enhancing, and segmenting the power-line data collected by UAVs, a UAV power-line presence recognition image dataset is obtained. Second, through comparative experiments with multi-attention modules, the dual-attention mechanism is selected to construct the CNN, and the UAV real-time power-line presence recognition training is conducted using the SGD optimiser and Hard-Swish activation function. Finally, knowledge distillation is employed to transfer the knowledge from the dual-attention mechanism-based CNN to the nonlinear function and Mamba-enhanced GhostNet v2 network, thereby reducing the model\u2019s parameter count and achieving real-time recognition performance suitable for mobile device deployment. Experiments demonstrate that the UAV-based real-time power-line presence recognition method proposed in this paper achieves real-time recognition accuracy rates of over 91.4% across all regions, providing a technical foundation for advancing the development and progress of UAV-based real-time power-line presence recognition.<\/jats:p>","DOI":"10.3390\/e28020166","type":"journal-article","created":{"date-parts":[[2026,2,2]],"date-time":"2026-02-02T09:48:08Z","timestamp":1770025688000},"page":"166","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GD-DAMNet: Real-Time UAV-Based Overhead Power-Line Presence Recognition Using a Lightweight Knowledge Distillation with Mamba-GhostNet v2 and Dual-Attention"],"prefix":"10.3390","volume":"28","author":[{"given":"Shuyu","family":"Sun","sequence":"first","affiliation":[{"name":"College of Engineering & Technical,  Chengdu University of Technology, Leshan 614000, China"}]},{"given":"Yingnan","family":"Xiao","sequence":"additional","affiliation":[{"name":"College of Engineering & Technical,  Chengdu University of Technology, Leshan 614000, China"}]},{"given":"Gaoping","family":"Li","sequence":"additional","affiliation":[{"name":"School of Mathematics, Southwest Minzu University, Chengdu 610041, China"}]},{"given":"Yuyan","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Artificial Intelligence, Southwest Minzu University, Chengdu 610041, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1186-7289","authenticated-orcid":false,"given":"Ying","family":"Tan","sequence":"additional","affiliation":[{"name":"School of Mathematics, Southwest Minzu University, Chengdu 610041, China"}]},{"given":"Jundong","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Computer Science and Artificial Intelligence, Southwest Minzu University, Chengdu 610041, China"}]},{"given":"Yifan","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Computer Science and Artificial Intelligence, Southwest Minzu University, Chengdu 610041, China"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9350","DOI":"10.1109\/TIM.2020.3031194","article-title":"A review on state-of-the-art power line inspection techniques","volume":"69","author":"Yang","year":"2020","journal-title":"IEEE Trans. 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