{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T17:19:01Z","timestamp":1740158341611,"version":"3.37.3"},"reference-count":42,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T00:00:00Z","timestamp":1645401600000},"content-version":"unspecified","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":"publisher","award":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"],"award-info":[{"award-number":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018551","name":"Science and Technology Innovation Talents in Universities of Henan Province","doi-asserted-by":"publisher","award":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"],"award-info":[{"award-number":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"]}],"id":[{"id":"10.13039\/501100018551","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006407","name":"Natural Science Foundation of Henan Province","doi-asserted-by":"publisher","award":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"],"award-info":[{"award-number":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"]}],"id":[{"id":"10.13039\/501100006407","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhongyuan Science and Technology Innovation Leadership Program","award":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"],"award-info":[{"award-number":["61873246","62072416","62006213","6167241","61702462","21HASTIT028","202300410495","214200510026"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2022,2,21]]},"abstract":"<jats:p>Deep learning has brought revolutionary progress to computer vision, so intelligent inspection equipment based on computer vision has developed rapidly. However, due to the large number of existing deep features, it is difficult to deploy it on mobile devices to achieve real-time tracking speed. This paper presents a target-aware deep feature compression for power intelligent inspection tracking. First, a negative balance loss function is designed to mine channel features suitable for the current inspection scene by shrinking the contribution of pure background negative samples and enhancing the impact of difficult negative samples. Based on this, the deep feature compression model is combined with Siamese tracking framework to achieve real-time and robust tracking. Finally, we evaluate the proposed method on real application scenarios and general data to prove the practicability of the proposed method.<\/jats:p>","DOI":"10.1155\/2022\/3161551","type":"journal-article","created":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T21:35:24Z","timestamp":1645479324000},"page":"1-10","source":"Crossref","is-referenced-by-count":0,"title":["Target-Aware Deep Feature Compression for Power Intelligent Inspection Tracking"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5459-1510","authenticated-orcid":true,"given":"Wei","family":"Jiang","sequence":"first","affiliation":[{"name":"State Grid Corporation of China, Beijing 100032, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9329-8659","authenticated-orcid":true,"given":"Zhimin","family":"Guo","sequence":"additional","affiliation":[{"name":"State Grid Henan Electric Power Research Institute, Zhengzhou 450000, China"}]},{"given":"Huanlong","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"}]},{"given":"Liyun","family":"Cheng","sequence":"additional","affiliation":[{"name":"College of Electric and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China"}]},{"given":"Yangyang","family":"Tian","sequence":"additional","affiliation":[{"name":"State Grid Henan Electric Power Research Institute, Zhengzhou 450000, China"}]}],"member":"311","reference":[{"doi-asserted-by":"publisher","key":"1","DOI":"10.1155\/2021\/5079607"},{"doi-asserted-by":"publisher","key":"2","DOI":"10.1155\/2012\/560541"},{"doi-asserted-by":"publisher","key":"3","DOI":"10.1109\/access.2021.3057659"},{"doi-asserted-by":"publisher","key":"4","DOI":"10.1186\/s41601-020-00166-8"},{"doi-asserted-by":"publisher","key":"5","DOI":"10.1186\/s41601-019-0145-1"},{"doi-asserted-by":"publisher","key":"6","DOI":"10.1163\/016918610x487117"},{"doi-asserted-by":"publisher","key":"7","DOI":"10.1177\/1729881417752821"},{"doi-asserted-by":"publisher","key":"8","DOI":"10.1155\/2014\/783810"},{"doi-asserted-by":"publisher","key":"9","DOI":"10.1155\/2018\/5381962"},{"doi-asserted-by":"publisher","key":"10","DOI":"10.1109\/iccvw.2015.84"},{"doi-asserted-by":"publisher","key":"11","DOI":"10.1155\/2015\/529724"},{"author":"P. Molchanov","article-title":"Pruning convolutional neural networks for resource efficient transfer learning","key":"12"},{"doi-asserted-by":"publisher","key":"13","DOI":"10.1109\/ICCV.2017.541"},{"doi-asserted-by":"publisher","key":"14","DOI":"10.1109\/cvpr.2017.574"},{"issue":"1","key":"15","first-page":"6869","article-title":"Quantized neural networks: training neural networks with low precision weights and activations","volume":"18","author":"I. Hubara","year":"2017","journal-title":"Journal of Machine Learning Research"},{"issue":"3","key":"16","first-page":"952","article-title":"Training CNNs with low-rank filters for efficient image classification","volume":"62","author":"Y. Ioannou","year":"2015","journal-title":"Journal of Asian Studies"},{"author":"C. Tai","article-title":"Convolutional neural networks with low-rank regularization","key":"17"},{"doi-asserted-by":"publisher","key":"18","DOI":"10.1109\/cvpr.2017.195"},{"author":"F. N. Iandola","article-title":"Squeezenet: alexnetlevel accuracy with 50x fewer parameters and <1mb model size","key":"19"},{"key":"20","first-page":"38","article-title":"Distilling the knowledge in a neural network","volume-title":"Computer Science","author":"G. Hinton"},{"author":"S. Zagoruyko","article-title":"Paying more attention to attention: improving the performance of convolutional neural networks via attention transfer","key":"21"},{"doi-asserted-by":"publisher","key":"22","DOI":"10.1109\/access.2017.2765626"},{"doi-asserted-by":"publisher","key":"23","DOI":"10.1109\/cvpr.2017.733"},{"doi-asserted-by":"publisher","key":"24","DOI":"10.1109\/cvpr.2018.00057"},{"doi-asserted-by":"publisher","key":"25","DOI":"10.1109\/cvpr.2019.00146"},{"doi-asserted-by":"publisher","key":"26","DOI":"10.1109\/tip.2018.2819362"},{"doi-asserted-by":"publisher","key":"27","DOI":"10.1109\/cvpr.2018.00937"},{"doi-asserted-by":"publisher","key":"28","DOI":"10.1007\/978-3-030-01264-9_22"},{"doi-asserted-by":"publisher","key":"29","DOI":"10.1109\/iccv.2019.00628"},{"doi-asserted-by":"publisher","key":"30","DOI":"10.3390\/s19214738"},{"doi-asserted-by":"publisher","key":"31","DOI":"10.1016\/j.ijepes.2017.12.016"},{"doi-asserted-by":"publisher","key":"32","DOI":"10.1109\/tip.2015.2482905"},{"doi-asserted-by":"publisher","key":"33","DOI":"10.1109\/tpami.2014.2388226"},{"doi-asserted-by":"publisher","key":"34","DOI":"10.1007\/978-3-319-46448-0_27"},{"doi-asserted-by":"publisher","key":"35","DOI":"10.1145\/2733373.2807412"},{"author":"K. Simonyan","article-title":"Very deep convolutional networks for large-scale image recognition","key":"36"},{"doi-asserted-by":"publisher","key":"37","DOI":"10.1007\/978-3-642-33765-9_50"},{"doi-asserted-by":"publisher","key":"38","DOI":"10.5244\/c.28.65"},{"doi-asserted-by":"publisher","key":"39","DOI":"10.1109\/TPAMI.2014.2345390"},{"doi-asserted-by":"publisher","key":"40","DOI":"10.1109\/iccv.2015.352"},{"doi-asserted-by":"publisher","key":"41","DOI":"10.1109\/iccv.2017.279"},{"doi-asserted-by":"publisher","key":"42","DOI":"10.1109\/cvpr.2018.00935"}],"container-title":["Journal of Electrical and Computer Engineering"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2022\/3161551.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2022\/3161551.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/jece\/2022\/3161551.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T21:35:32Z","timestamp":1645479332000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/jece\/2022\/3161551\/"}},"subtitle":[],"editor":[{"given":"Yang","family":"Li","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,2,21]]},"references-count":42,"alternative-id":["3161551","3161551"],"URL":"https:\/\/doi.org\/10.1155\/2022\/3161551","relation":{},"ISSN":["2090-0155","2090-0147"],"issn-type":[{"type":"electronic","value":"2090-0155"},{"type":"print","value":"2090-0147"}],"subject":[],"published":{"date-parts":[[2022,2,21]]}}}