{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:07:26Z","timestamp":1763345246466,"version":"3.45.0"},"reference-count":32,"publisher":"Tech Science Press","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.067867","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T08:31:53Z","timestamp":1754641913000},"page":"751-768","source":"Crossref","is-referenced-by-count":0,"title":["Marine Ship Detection Based on Twin Feature Pyramid Network and Spatial Attention"],"prefix":"10.32604","volume":"85","author":[{"given":"Huagang","family":"Jin","sequence":"first","affiliation":[]},{"given":"Yu","family":"Zhou","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"042611","DOI":"10.1117\/1.JRS.11.042611","article-title":"Ship detection in optical remote sensing images based on deep convolutional neural networks","volume":"11","author":"Yao","year":"2017","journal-title":"J Appl Remote Sens"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"8983","DOI":"10.1109\/TGRS.2019.2923988","article-title":"Dense attention pyramid networks for multi-scale ship detection in SAR images","volume":"57","author":"Cui","year":"2019","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1016\/0734-189X(86)90002-2","article-title":"Introduction to mathematical morphology","volume":"35","author":"Serra","year":"1986","journal-title":"Comput Vis Graph Image Process"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1109\/TPAMI.2012.89","article-title":"State-of-the-art in visual attention modeling","volume":"35","author":"Borji","year":"2012","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.cviu.2007.09.014","article-title":"Speeded-up robust features (SURF)","volume":"110","author":"Bay","year":"2008","journal-title":"Comput Vis Image Underst"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1080\/07038992.2000.10874770","article-title":"Validation of ship detection by the RADARSAT synthetic aperture radar and the ocean monitoring workstation","volume":"26","author":"Vachon","year":"2000","journal-title":"Can J Remote Sens"},{"article-title":"Rich feature hierarchies for accurate object detection and semantic segmentation","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2014 Jun 23\u201328; Columbus, OH, USA","author":"Girshick","key":"ref7"},{"article-title":"Fast R-CNN","series-title":"Proceedings of the IEEE International Conference on Computer Vision; 2015 Dec 7\u201313; Washington, DC, USA","author":"Girshick","key":"ref8"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","article-title":"Faster R-CNN: towards real-time object detection with region proposal networks","volume":"39","author":"Ren","year":"2016","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"article-title":"SSD: single shot multibox detector","series-title":"Proceedings of the Computer Vision\u2014ECCV 2016: 14th European Conference; 2016 Oct 11\u201314; Amsterdam, The Netherlands","author":"Liu","key":"ref10"},{"article-title":"You only look once: unified, real-time object detection","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2016 Jun 27\u201330; Las Vegas, NV, USA","author":"Redmon","key":"ref11"},{"article-title":"Feature pyramid networks for object detection","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2017 Jul 21\u201326; Honolulu, HI, USA","author":"Lin","key":"ref12"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"15547","DOI":"10.1007\/s10489-022-03220-0","article-title":"Attention-based fusion factor in FPN for object detection","volume":"52","author":"Li","year":"2022","journal-title":"Appl Intell"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"013009","DOI":"10.1117\/1.JEI.31.1.013009","article-title":"Dual-bottleneck feature pyramid network for multiscale object detection","volume":"31","author":"Chen","year":"2022","journal-title":"J Electron Imaging"},{"article-title":"Effective fusion factor in FPN for tiny object detection","series-title":"Proceedings of the IEEE\/CVF Winter Conference on Applications of Computer Vision; 2021 Jan 3\u20138; Waikoloa, HI, USA","author":"Gong","key":"ref15"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"3372","DOI":"10.1109\/TCSVT.2019.2950526","article-title":"High-level semantic networks for multi-scale object detection","volume":"30","author":"Cao","year":"2019","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"article-title":"AugFPN: improving multi-scale feature learning for object detection","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition; 2020 Jun 13\u201319; Seattle, WA, USA","author":"Guo","key":"ref17"},{"article-title":"NAS-FPN: learning scalable feature pyramid architecture for object detection","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition; 2019 Jun 15\u201320; Long Beach, CA, USA","author":"Ghiasi","key":"ref18"},{"article-title":"EfficientDet: scalable and efficient object detection","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition; 2020 Jun 13\u201319; Seattle, WA, USA","author":"Tan","key":"ref19"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"108437","DOI":"10.1016\/j.patcog.2021.108437","article-title":"Adaptive region-aware feature enhancement for object detection","volume":"124","author":"Fan","year":"2022","journal-title":"Pattern Recognit"},{"article-title":"Attention-based network for low-light image enhancement","series-title":"Proceedings of the 2020 IEEE International Conference on Multimedia and Expo (ICME); 2020 Jul 6\u201310; London, UK","author":"Zhang","key":"ref21"},{"article-title":"Squeeze-and-excitation networks","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition; 2018 Jun 18\u201323; Salt Lake City, UT, USA","author":"Hu","key":"ref22"},{"article-title":"CBAM: convolutional block attention module","series-title":"Proceedings of the European Conference on Computer Vision (ECCV); 2018 Sep 8\u201314; Munich, Germany","author":"Woo","key":"ref23"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"2359","DOI":"10.1016\/j.procs.2023.01.211","article-title":"Attention over attention: an enhanced supervised video summarization approach","volume":"218","author":"Puthige","year":"2023","journal-title":"Procedia Comput Sci"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"6221545","DOI":"10.1155\/2021\/6221545","article-title":"Bearing faulty prognostic approach based on multiscale feature extraction and attention learning mechanism","volume":"2021","author":"Zhou","year":"2021","journal-title":"J Sens"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"104658","DOI":"10.1016\/j.imavis.2023.104658","article-title":"Language and vision based person re-identification for surveillance systems using deep learning with LIP layers","volume":"132","author":"Bukhari","year":"2023","journal-title":"Image Vis Comput"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"4611","DOI":"10.1007\/s00521-020-05237-3","article-title":"ATP-DenseNet: a hybrid deep learning-based gender identification of handwriting","volume":"33","author":"Xue","year":"2021","journal-title":"Neural Comput Appl"},{"key":"ref28","doi-asserted-by":"crossref","first-page":"2921","DOI":"10.3390\/rs11242921","article-title":"HDRANet: hybrid dilated residual attention network for SAR image despeckling","volume":"11","author":"Li","year":"2019","journal-title":"Remote Sens"},{"article-title":"ResNeSt: split-attention networks","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition; 2022 Jun 19\u201320; New Orleans, LA, USA","author":"Zhang","key":"ref29"},{"article-title":"Focal loss for dense object detection","series-title":"Proceedings of the IEEE International Conference on Computer Vision; 2017 Oct 22\u201329; Venice, Italy","author":"Lin","key":"ref30"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"2152","DOI":"10.1109\/LSP.2021.3099746","article-title":"Two-branch deep neural network for underwater image enhancement in HSV color space","volume":"28","author":"Hu","year":"2021","journal-title":"IEEE Signal Process Lett"},{"key":"ref32","first-page":"103975","article-title":"Advanced ship detection and ocean monitoring with satellite imagery and deep learning for marine science applications","volume":"81","author":"Bakirci","year":"2025","journal-title":"Reg Stud Mar Sci"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-85-1\/TSP_CMC_67867\/TSP_CMC_67867.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:03:18Z","timestamp":1763344998000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v85n1\/63574"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":32,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.067867","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]}}}