{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T14:24:54Z","timestamp":1780496694257,"version":"3.54.1"},"reference-count":57,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T00:00:00Z","timestamp":1749254400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T00:00:00Z","timestamp":1749254400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Scientific Research Program Funded by Education Department of Shaanxi Provincial Government","award":["22JY025"],"award-info":[{"award-number":["22JY025"]}]},{"name":"Scientific Research Program Funded by Education Department of Shaanxi Provincial Government","award":["22JY025"],"award-info":[{"award-number":["22JY025"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-07485-3","type":"journal-article","created":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T10:39:05Z","timestamp":1749292745000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["FP-RTDETR: enhancing infrared ship detection with multi-scale feature fusion and lightweight design"],"prefix":"10.1007","volume":"81","author":[{"given":"Xi","family":"Chen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guohui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,6,7]]},"reference":[{"key":"7485_CR1","doi-asserted-by":"publisher","first-page":"105107","DOI":"10.1016\/j.infrared.2023.105107","volume":"137","author":"Z Hou","year":"2024","unstructured":"Hou Z et al (2024) An object detection algorithm based on infrared-visible dual modal feature fusion. Infrared Phys Technol 137:105107","journal-title":"Infrared Phys Technol"},{"key":"7485_CR2","doi-asserted-by":"publisher","first-page":"130442","DOI":"10.1016\/j.optcom.2024.130442","volume":"559","author":"J Wang","year":"2024","unstructured":"Wang J et al (2024) Analysis and research on polarized radiation characteristics of ship targets at sea. Opt Commun 559:130442","journal-title":"Opt Commun"},{"key":"7485_CR3","doi-asserted-by":"crossref","unstructured":"Morillas JR, Garc\u00eda IC, Z\u00f6lzer U (2015) Ship detection based on SVM using color and texture features. In: 2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). IEEE","DOI":"10.1109\/ICCP.2015.7312682"},{"issue":"6","key":"7485_CR4","doi-asserted-by":"publisher","first-page":"159","DOI":"10.3390\/ijgi6060159","volume":"6","author":"T Nie","year":"2017","unstructured":"Nie T et al (2017) A method of ship detection under complex background. ISPRS Int J Geo-Inf 6(6):159","journal-title":"ISPRS Int J Geo-Inf"},{"issue":"3","key":"7485_CR5","first-page":"94","volume":"16","author":"M Ding","year":"2019","unstructured":"Ding M et al (2019) Infrared target detection and recognition method in airborne photoelectric system. J Aerosp Inf Syst 16(3):94\u2013106","journal-title":"J Aerosp Inf Syst"},{"issue":"5","key":"7485_CR6","doi-asserted-by":"publisher","first-page":"418","DOI":"10.1049\/cvi2.12097","volume":"16","author":"Z Xing","year":"2022","unstructured":"Xing Z, Chen Xi, Pang F (2022) DD-YOLO: An object detection method combining knowledge distillation and differentiable architecture search. IET Comput Vision 16(5):418\u2013430","journal-title":"IET Comput Vision"},{"issue":"1","key":"7485_CR7","doi-asserted-by":"publisher","first-page":"2285292","DOI":"10.1080\/21642583.2023.2285292","volume":"11","author":"F Pang","year":"2023","unstructured":"Pang F, Chen Xi (2023) MS-YOLOv5: a lightweight algorithm for strawberry ripeness detection based on deep learning. Syst Sci Control Eng 11(1):2285292","journal-title":"Syst Sci Control Eng"},{"key":"7485_CR8","unstructured":"Liu W, Anguelov D, Erhan D, Szegedy C, Reed S, Fu CY, Berg AC (2016) Ssd: single shot multibox detector. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part I 14. Springer International Publishing"},{"issue":"2","key":"7485_CR9","first-page":"170","volume":"43","author":"GU Jiaojiao","year":"2021","unstructured":"Jiaojiao GU et al (2021) Infrared ship target detection algorithm based on improved faster R-CNN. Infrared Technol 43(2):170\u2013178","journal-title":"Infrared Technol"},{"issue":"6","key":"7485_CR10","doi-asserted-by":"publisher","first-page":"e0303451","DOI":"10.1371\/journal.pone.0303451","volume":"19","author":"Z Hao","year":"2024","unstructured":"Hao Z et al (2024) YOLO-ISTD: an infrared small target detection method based on YOLOv5-S. PLoS ONE 19(6):e0303451","journal-title":"PLoS ONE"},{"key":"7485_CR11","doi-asserted-by":"crossref","unstructured":"Zhao Y, Lv W, Xu S, Wei J, Wang G, Dang Q, Liu Y, Chen J (2024) Detrs beat yolos on real-time object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR52733.2024.01605"},{"key":"7485_CR12","doi-asserted-by":"crossref","unstructured":"Wang S, Wang S, Wan Y, Xiao Z (2024) Residual cross-stage parallel method of drone images based on real-time detection with transformer. In: 2024 6th International Conference on Internet of Things, Automation and Artificial Intelligence (IoTAAI). IEEE","DOI":"10.1109\/IoTAAI62601.2024.10692694"},{"issue":"12","key":"7485_CR13","doi-asserted-by":"publisher","first-page":"2130","DOI":"10.3390\/jmse12122130","volume":"12","author":"C Liu","year":"2024","unstructured":"Liu C et al (2024) Improved RT-DETR for infrared ship detection based on multi-attention and feature fusion. J Mar Sci Eng 12(12):2130","journal-title":"J Mar Sci Eng"},{"key":"7485_CR14","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.compag.2017.03.016","volume":"137","author":"MA Ebrahimi","year":"2017","unstructured":"Ebrahimi MA et al (2017) Vision-based pest detection based on SVM classification method. Comput Electron Agric 137:52\u201358","journal-title":"Comput Electron Agric"},{"issue":"1","key":"7485_CR15","doi-asserted-by":"publisher","first-page":"340","DOI":"10.1109\/JSEN.2017.2771226","volume":"18","author":"S Zidi","year":"2017","unstructured":"Zidi S, Moulahi T, Alaya B (2017) Fault detection in wireless sensor networks through SVM classifier. IEEE Sens J 18(1):340\u2013347","journal-title":"IEEE Sens J"},{"issue":"4","key":"7485_CR16","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1016\/j.sigpro.2010.08.010","volume":"91","author":"Y Pang","year":"2011","unstructured":"Pang Y et al (2011) Efficient HOG human detection. Signal Process 91(4):773\u2013781","journal-title":"Signal Process"},{"key":"7485_CR17","doi-asserted-by":"publisher","first-page":"13363","DOI":"10.1007\/s11042-017-4952-y","volume":"77","author":"L Huang","year":"2018","unstructured":"Huang L et al (2018) Multiple features learning for ship classification in optical imagery. Multimedia Tools Appl 77:13363\u201313389","journal-title":"Multimedia Tools Appl"},{"key":"7485_CR18","first-page":"3296495","volume":"2022","author":"K Li","year":"2022","unstructured":"Li K, Yu H, Xu Y, Luo X (2022) Detection of marine oil spills based on HOG feature and SVM classifier. J Sen 2022:3296495","journal-title":"J Sen"},{"key":"7485_CR19","doi-asserted-by":"crossref","unstructured":"Arguedas VF (2015) Texture-based vessel classifier for electro-optical satellite imagery. In: 2015 IEEE International Conference on Image Processing (ICIP). IEEE","DOI":"10.1109\/ICIP.2015.7351529"},{"key":"7485_CR20","doi-asserted-by":"crossref","unstructured":"Ju H (2015) Ship detection for high resolution optical imagery with adaptive target filter. In: AOPC 2015: Image Processing and Analysis. vol. 9675. SPIE","DOI":"10.1117\/12.2202960"},{"key":"7485_CR21","unstructured":"Xu G, Wang J, Qi S (2018) Ship detection based on rotation-invariant HOG descriptors for airborne infrared images. In: MIPPR 2017: Pattern Recognition and Computer Vision. vol. 10609. SPIE"},{"issue":"8","key":"7485_CR22","first-page":"188","volume":"34","author":"Y Cao","year":"2023","unstructured":"Cao Y et al (2023) Improved infrared target detection algorithm of YOLOv3. J Electron Measurement Instrum 34(8):188\u2013194","journal-title":"J Electron Measurement Instrum"},{"issue":"14","key":"7485_CR23","doi-asserted-by":"publisher","first-page":"2774","DOI":"10.3390\/electronics13142774","volume":"13","author":"S Yang","year":"2024","unstructured":"Yang S et al (2024) Maritime electro-optical image object matching based on improved YOLOv9. Electronics 13(14):2774","journal-title":"Electronics"},{"key":"7485_CR24","doi-asserted-by":"publisher","first-page":"107742","DOI":"10.1016\/j.engappai.2023.107742","volume":"130","author":"X Chen","year":"2024","unstructured":"Chen X et al (2024) Ship imaging trajectory extraction via an aggregated you only look once (YOLO) model. Eng Appl Artif Intell 130:107742","journal-title":"Eng Appl Artif Intell"},{"issue":"2","key":"7485_CR25","doi-asserted-by":"publisher","first-page":"213","DOI":"10.3390\/jmse12020213","volume":"12","author":"Y Wang","year":"2024","unstructured":"Wang Y et al (2024) GT-YOLO: nearshore infrared ship detection based on infrared images. J Mar Sci Eng 12(2):213","journal-title":"J Mar Sci Eng"},{"key":"7485_CR26","unstructured":"Li Z et al (2024) SpecDETR: A Transformer-Based Hyperspectral Point Object Detection Network. arxiv preprint arxiv: 2405.10148"},{"issue":"6","key":"7485_CR27","doi-asserted-by":"publisher","first-page":"240","DOI":"10.3390\/drones8060240","volume":"8","author":"S Wang","year":"2024","unstructured":"Wang S et al (2024) PHSI-rtdetr: a lightweight infrared small target detection algorithm based on UAV aerial photography. Drones 8(6):240","journal-title":"Drones"},{"key":"7485_CR28","doi-asserted-by":"crossref","unstructured":"Ma X et al (2024) Rewrite the stars. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR52733.2024.00544"},{"key":"7485_CR29","unstructured":"Guo J et al (2024) SLAB: efficient transformers with simplified linear attention and progressive re-parameterized batch normalization. In: Proceedings of the 41st International Conference on Machine Learning (ICML\u201924), vol. 235, pp 16802\u201316812"},{"key":"7485_CR30","doi-asserted-by":"crossref","unstructured":"Xu S et al (2024) Hcf-net: hierarchical context fusion network for infrared small object detection. In: 2024 IEEE International Conference on Multimedia and Expo (ICME). IEEE","DOI":"10.1109\/ICME57554.2024.10687431"},{"key":"7485_CR31","unstructured":"Song Y et al (2022) Rethinking performance gains in image dehazing networks. arxiv preprint arxiv: 2209.11448"},{"key":"7485_CR32","first-page":"9204","volume":"34","author":"H Liu","year":"2021","unstructured":"Liu H et al (2021) Pay attention to mlps. Adv Neural Inf Process Syst 34:9204\u20139215","journal-title":"Adv Neural Inf Process Syst"},{"key":"7485_CR33","unstructured":"Shazeer N (2020) Glu variants improve transformer. arxiv preprint arxiv:2002.05202"},{"key":"7485_CR34","unstructured":"Ioffe S, Szegedy C (2015) Batch normalization: accelerating deep network training by reducing internal covariate shift. In: International Conference on Machine Learning. PMLR"},{"key":"7485_CR35","unstructured":"InfiRay Dataset [OL]. Available online:\u00a0http:\/\/openai.iraytek.com\/apply\/Sea_shipping.html\/. Accessed on 06 Oct 2024"},{"issue":"1","key":"7485_CR36","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1038\/s41597-023-02066-6","volume":"10","author":"J Suo","year":"2023","unstructured":"Suo J et al (2023) HIT-UAV: a high-altitude infrared thermal dataset for unmanned aerial vehicle-based object detection. Sci Data 10(1):227","journal-title":"Sci Data"},{"issue":"3","key":"7485_CR37","doi-asserted-by":"publisher","first-page":"1244","DOI":"10.1007\/s10489-020-01882-2","volume":"51","author":"X Dai","year":"2021","unstructured":"Dai X, Yuan X, Wei X (2021) TIRNet: object detection in thermal infrared images for autonomous driving. Appl Intell 51(3):1244\u20131261","journal-title":"Appl Intell"},{"key":"7485_CR38","doi-asserted-by":"crossref","unstructured":"Qi Y et al (2023) Dynamic snake convolution based on topological geometric constraints for tubular structure segmentation. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision","DOI":"10.1109\/ICCV51070.2023.00558"},{"key":"7485_CR39","doi-asserted-by":"crossref","unstructured":"Salman H et al (2023) Orthonets: orthogonal channel attention networks. In: 2023 IEEE International Conference on Big Data (BigData). IEEE","DOI":"10.1109\/BigData59044.2023.10386646"},{"key":"7485_CR40","doi-asserted-by":"crossref","unstructured":"Ding, Xiaohan et al (2021) Diverse branch block: Building a convolution as an inception-like unit. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR46437.2021.01074"},{"key":"7485_CR41","doi-asserted-by":"publisher","first-page":"102709","DOI":"10.1016\/j.aei.2024.102709","volume":"62","author":"D Wan","year":"2024","unstructured":"Wan D et al (2024) YOLO-MIF: Improved yolov8 with multi-information fusion for object detection in gray-scale images. Adv Eng Inform 62:102709","journal-title":"Adv Eng Inform"},{"key":"7485_CR42","doi-asserted-by":"crossref","unstructured":"Shaker A et al (2023) Swiftformer: efficient additive attention for transformer-based real-time mobile vision applications. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision","DOI":"10.1109\/ICCV51070.2023.01598"},{"key":"7485_CR43","doi-asserted-by":"crossref","unstructured":"Xia Z et al (2022) Vision transformer with deformable attention. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","DOI":"10.1109\/CVPR52688.2022.00475"},{"key":"7485_CR44","first-page":"1","volume":"61","author":"H Wu","year":"2023","unstructured":"Wu H et al (2023) CMTFNet: CNN and multiscale transformer fusion network for remote-sensing image semantic segmentation. IEEE Trans Geosci Remote Sens 61:1\u201312","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"7485_CR45","doi-asserted-by":"crossref","unstructured":"Li Y, Dua A, Ren F (2020) Light-weight RetinaNet for object detection on edge devices. In: 2020 IEEE 6th World Forum on Internet of Things (WF-IoT). IEEE","DOI":"10.1109\/WF-IoT48130.2020.9221150"},{"issue":"6","key":"7485_CR46","doi-asserted-by":"publisher","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren S et al (2016) Faster R-CNN: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"7485_CR47","volume-title":"Computer Vision and Pattern Recognition","author":"A Farhadi","year":"2018","unstructured":"Farhadi A, Redmon J (2018) Yolov3: An incremental improvement. Computer Vision and Pattern Recognition, vol 1804. Springer, Germany"},{"key":"7485_CR48","unstructured":"Jocher G et al (2021) ultralytics\/yolov5: v6. 0-YOLOv5n \u2018Nano\u2019 models, Roboflow integration, TensorFlow export, OpenCV DNN support. Zenodo"},{"key":"7485_CR49","volume-title":"International conference on data intelligence and cognitive informatics","author":"M Sohan","year":"2024","unstructured":"Sohan M et al (2024) A review on yolov8 and its advancements. International conference on data intelligence and cognitive informatics. Springer, Singapore"},{"key":"7485_CR50","volume-title":"European conference on computer vision","author":"C-Y Wang","year":"2025","unstructured":"Wang C-Y, Yeh I-H, MarkLiao H-Y (2025) Yolov9: learning what you want to learn using programmable gradient information. European conference on computer vision. Springer, Cham"},{"issue":"2024","key":"7485_CR51","first-page":"107984","volume":"37","author":"A Wang","year":"2024","unstructured":"Wang A et al (2024) Yolov10: real-time end-to-end object detection. Adv Neural Inf Process Syst 37(2024):107984\u2013108011","journal-title":"Adv Neural Inf Process Syst"},{"key":"7485_CR52","unstructured":"Jocher G, Qiu J (2024) Ultralytics YOLOv11. Ultralytics YOLO Docs. https:\/\/docs.ultralytics.com\/models\/yolo11\/"},{"key":"7485_CR53","unstructured":"Tian Y, Ye Q, Doermann D (2025) Yolov12: attention-centric real-time object detectors. arxiv preprint arxiv: 2502.12524"},{"key":"7485_CR54","doi-asserted-by":"crossref","unstructured":"Feng Y et al (2024) Hyper-yolo: When visual object detection meets hypergraph computation. In: IEEE Transactions on Pattern Analysis and Machine Intelligence.","DOI":"10.1109\/TPAMI.2024.3524377"},{"issue":"4","key":"7485_CR55","doi-asserted-by":"publisher","first-page":"045246","DOI":"10.1088\/2631-8695\/ad97a4","volume":"6","author":"Qi Chen","year":"2024","unstructured":"Chen Qi, Lv Z (2024) AKS-YOLOv8: a lightweight and accurate network model for infrared ship detection. Eng Res Express 6(4):045246","journal-title":"Eng Res Express"},{"key":"7485_CR56","unstructured":"Li C et al (2022) YOLOv6: a single-stage object detection framework for industrial applications. arXiv preprint arXiv:2209.02976"},{"key":"7485_CR57","doi-asserted-by":"crossref","unstructured":"Selvaraju RR et al (2017) Grad-cam: Visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE international conference on computer vision","DOI":"10.1109\/ICCV.2017.74"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07485-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07485-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07485-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,7]],"date-time":"2025-06-07T10:39:23Z","timestamp":1749292763000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07485-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,7]]},"references-count":57,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2025,6]]}},"alternative-id":["7485"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07485-3","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,7]]},"assertion":[{"value":"20 May 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 June 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"984"}}