{"id":654,"date":"2023-10-07T16:24:13","date_gmt":"2023-10-07T08:24:13","guid":{"rendered":"http:\/\/124.221.8.228\/?page_id=654"},"modified":"2023-10-07T17:32:49","modified_gmt":"2023-10-07T09:32:49","slug":"2022%e5%b9%b4","status":"publish","type":"page","link":"http:\/\/106.54.160.89\/index.php\/2022%e5%b9%b4\/","title":{"rendered":"2022\u5e74"},"content":{"rendered":"\n
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DRR-Net: A Dense-Connected Residual Recurrent Convolutional Network for Surgical Instrument Segmentation From Endoscopic Images<\/strong><\/a><\/p>\n\n\n\n

Lei Yang,\u00a0Yuge Gu,\u00a0Guibin Bian,\u00a0Yanhong Liu<\/p>\n\n\n\n

IEEE Transactions on Medical Robotics and Bionics.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/tmrb.2022.3193420<\/p>\n<\/div>\n\n\n\n

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TMF-Net: A Transformer-Based Multiscale Fusion Network for Surgical Instrument Segmentation From Endoscopic Images<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Yuge Gu,\u00a0Guibin Bian,\u00a0Yanhong Liu<\/p>\n\n\n\n

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/tim.2022.3225922<\/p>\n<\/div>\n\n\n\n

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TAR-Net: A Triple Attention Residual Network for Power Line Extraction from Infrared Aerial Images<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Shuyi Kong,\u00a0Hanyun Huang,\u00a0Heng Li<\/p>\n\n\n\n

Lecture Notes in Computer Science.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1007\/978-3-031-20497-5_53<\/p>\n<\/div>\n\n\n\n

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An Efficient End-to-End CNN Network for High-voltage Transmission Line Segmentation<\/a><\/strong><\/p>\n\n\n\n

Lei Yang, Shuyi Kong, Shilong Cui, Hanyun Huang, Yanhong Liu<\/p>\n\n\n\n

02022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS).<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/ccis57298.2022.10016321<\/p>\n<\/div>\n\n\n\n

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DEF-Net: A Dual-Encoder Fusion Network for Fundus Retinal Vessel Segmentation<\/a><\/strong><\/p>\n\n\n\n

Jianyong Li,\u00a0Ge Gao,\u00a0Lei Yang,\u00a0Yanhong Liu,\u00a0Hongnian Yu<\/p>\n\n\n\n

Electronics.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.3390\/electronics11223810<\/p>\n<\/div>\n\n\n\n

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Insulator Fault Diagnosis Based on Improved Transfer Learning from UAV Images<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Ji Shen,\u00a0Man Wu,\u00a0Yanhong Liu<\/p>\n\n\n\n

2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC).<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/smc53654.2022.9945251<\/p>\n<\/div>\n\n\n\n

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A light defect detection algorithm of power insulators from aerial images for power inspection<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Junfeng Fan,\u00a0Shouan Song,\u00a0Yanhong Liu<\/p>\n\n\n\n

Neural Computing and Applications.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1007\/s00521-022-07437-5<\/p>\n<\/div>\n\n\n\n

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Image Denoising of Seam Images With Deep Learning for Laser Vision Seam Tracking<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Junfeng Fan,\u00a0Benyan Huo,\u00a0En Li,\u00a0Yanhong Liu<\/p>\n\n\n\n

IEEE SENSORS JOURNAL.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/jsen.2022.3147489<\/p>\n<\/div>\n\n\n\n

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An attention-guided network for surgical instrument segmentation from endoscopic images<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Yuge Gu,\u00a0Guibin Bian,\u00a0Yanhong Liu<\/p>\n\n\n\n

COMPUTERS IN BIOLOGY AND MEDICINE.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1016\/j.compbiomed.2022.106216<\/p>\n<\/div>\n\n\n\n

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Vision-Based Power Line Segmentation With an Attention Fusion Network<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Junfeng Fan,\u00a0Shuai Xu,\u00a0En Li,\u00a0Yanhong Liu<\/p>\n\n\n\n

IEEE SENSORS JOURNAL.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1109\/jsen.2022.3157336<\/p>\n<\/div>\n\n\n\n

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An Automatic Surface Defect Detection Method with Residual Attention Network<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Suli Bai,\u00a0Hanyun Huang,\u00a0Shuyi Kong<\/p>\n\n\n\n

Lecture Notes in Computer Science.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1007\/978-3-031-20500-2_16<\/p>\n<\/div>\n\n\n\n

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A nondestructive automatic defect detection method with pixelwise segmentation<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Junfeng Fan,\u00a0Benyan Huo,\u00a0En Li,\u00a0Yanhong Liu<\/p>\n\n\n\n

KNOWLEDGE-BASED SYSTEMS.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1016\/j.knosys.2022.108338<\/p>\n<\/div>\n\n\n\n

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PLE-Net: Automatic power line extraction method using deep learning from aerial images<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Junfeng Fan,\u00a0Benyan Huo,\u00a0En Li,\u00a0Yanhong Liu<\/p>\n\n\n\n

EXPERT SYSTEMS WITH APPLICATIONS.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1016\/j.eswa.2022.116771<\/p>\n\n\n\n

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A shape-guided deep residual network for automated CT lung segmentation<\/a><\/strong><\/p>\n\n\n\n

Lei Yang,\u00a0Yuge Gu,\u00a0Benyan Huo,\u00a0Yanhong Liu,\u00a0Guibin Bian<\/p>\n\n\n\n

KNOWLEDGE-BASED SYSTEMS.<\/em>2022<\/strong><\/p>\n\n\n\n

DOI\uff1a10.1016\/j.knosys.2022.108981<\/p>\n<\/div>\n\n\n\n

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DRR-Net: A Dense-Connected Residual Recurrent Convoluti […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-654","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/pages\/654","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/comments?post=654"}],"version-history":[{"count":2,"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/pages\/654\/revisions"}],"predecessor-version":[{"id":658,"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/pages\/654\/revisions\/658"}],"wp:attachment":[{"href":"http:\/\/106.54.160.89\/index.php\/wp-json\/wp\/v2\/media?parent=654"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}