{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T21:55:21Z","timestamp":1778795721817,"version":"3.51.4"},"reference-count":52,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T00:00:00Z","timestamp":1740355200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"DOI":"10.1007\/s11227-025-07003-5","type":"journal-article","created":{"date-parts":[[2025,2,24]],"date-time":"2025-02-24T21:08:47Z","timestamp":1740431327000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["MTGS-Yolo: a task-balanced algorithm for object detection in remote sensing images based on improved yolo"],"prefix":"10.1007","volume":"81","author":[{"given":"Zhao","family":"Jin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiang","family":"Duan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liping","family":"Qiao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tian","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyu","family":"Shi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bohan","family":"Yan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,2,24]]},"reference":[{"issue":"10","key":"7003_CR1","doi-asserted-by":"publisher","first-page":"2385","DOI":"10.3390\/rs14102385","volume":"14","author":"Z Li","year":"2022","unstructured":"Li Z, Wang Y, Zhang N et al (2022) Deep learning-based object detection techniques for remote sensing images: a survey[J]. Remote Sens 14(10):2385","journal-title":"Remote Sens"},{"issue":"1","key":"7003_CR2","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1080\/14498596.2008.9635134","volume":"53","author":"K Johansen","year":"2008","unstructured":"Johansen K, Roelfsema C, Phinn S (2008) High spatial resolution remote sensing for environmental monitoring and management preface[J]. J Spat Sci 53(1):43\u201347","journal-title":"J Spat Sci"},{"key":"7003_CR3","doi-asserted-by":"crossref","unstructured":"Bharatkar PS, Patel R (2013) Evaluation of rsi classification methods for effective land use mapping[C]. In: 2013 International Conference on Communication Systems and Network Technologies. IEEE, p 109\u2013113","DOI":"10.1109\/CSNT.2013.32"},{"key":"7003_CR4","doi-asserted-by":"publisher","first-page":"3436","DOI":"10.1016\/j.trpro.2016.05.303","volume":"14","author":"L Persia","year":"2016","unstructured":"Persia L, Usami DS, De Simone F et al (2016) Management of road infrastructure safety[J]. Transp Res Procedia 14:3436\u20133445","journal-title":"Transp Res Procedia"},{"key":"7003_CR5","doi-asserted-by":"crossref","unstructured":"Shi L, Kodagoda S, Dissanayake G (2010) Multi-class classification for semantic labeling of places[C]. In: 2010 11th International Conference on Control Automation Robotics & Vision. IEEE, p 2307\u20132312","DOI":"10.1109\/ICARCV.2010.5707856"},{"issue":"6","key":"7003_CR6","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1016\/j.omega.2009.12.001","volume":"38","author":"WD Cook","year":"2010","unstructured":"Cook WD, Liang L, Zhu J (2010) Measuring performance of two-stage network structures by DEA: a review and future perspective[J]. Omega 38(6):423\u2013430","journal-title":"Omega"},{"key":"7003_CR7","doi-asserted-by":"crossref","unstructured":"Girshick R (2015) Fast r-cnn[C]. In: Proceedings of the IEEE international conference on computer vision. p 1440\u20131448","DOI":"10.1109\/ICCV.2015.169"},{"key":"7003_CR8","doi-asserted-by":"crossref","unstructured":"Zhang Y, Li X, Wang F, et al (2021) A comprehensive review of one-stage networks for object detection[C]. In: 2021 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC). IEEE, p 1\u20136","DOI":"10.1109\/ICSPCC52875.2021.9564613"},{"issue":"20","key":"7003_CR9","doi-asserted-by":"publisher","first-page":"10879","DOI":"10.1007\/s00500-022-07106-8","volume":"26","author":"J Xue","year":"2022","unstructured":"Xue J, Zheng Y, Dong-Ye C et al (2022) Improved YOLOv5 network method for remote sensing image-based ground objects recognition[J]. Soft Comput 26(20):10879\u201310889","journal-title":"Soft Comput"},{"issue":"8","key":"7003_CR10","doi-asserted-by":"publisher","first-page":"6946","DOI":"10.1109\/TGRS.2020.3030990","volume":"59","author":"X Feng","year":"2020","unstructured":"Feng X, Han J, Yao X et al (2020) TCANet: triple context-aware network for weakly supervised object detection in remote sensing images[J]. IEEE Trans Geosci Remote Sens 59(8):6946\u20136955","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"7003_CR11","first-page":"1","volume":"61","author":"T Gao","year":"2023","unstructured":"Gao T, Liu Z, Zhang J et al (2023) A task-balanced multi-scale adaptive fusion network for object detection in remote sensing images[J]. IEEE Trans Geosci Remote Sens 61:1\u201315","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"7003_CR12","doi-asserted-by":"publisher","first-page":"104252","DOI":"10.1016\/j.oregeorev.2021.104252","volume":"136","author":"ST Thiele","year":"2021","unstructured":"Thiele ST, Lorenz S, Kirsch M et al (2021) Multi-scale, multi-sensor data integration for automated 3-D geological mapping[J]. Ore Geol Rev 136:104252","journal-title":"Ore Geol Rev"},{"key":"7003_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2024.3510781","volume":"62","author":"Y Zhang","year":"2024","unstructured":"Zhang Y, Ye M, Zhu G et al (2024) FFCA-YOLO for small object detection in remote sensing images[J]. IEEE Trans Geosci Remote Sens 62:1\u201315","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"3","key":"7003_CR14","doi-asserted-by":"publisher","first-page":"625","DOI":"10.1111\/coin.12232","volume":"35","author":"K Ogura","year":"2019","unstructured":"Ogura K, Yamada Y, Kajita S et al (2019) Ground object recognition and segmentation from aerial image-based 3D point cloud[J]. Comput Intell 35(3):625\u2013642","journal-title":"Comput Intell"},{"key":"7003_CR15","unstructured":"Decision making in complex environments[M] (2007) Ashgate Publishing, Ltd."},{"key":"7003_CR16","doi-asserted-by":"crossref","unstructured":"Baqu\u00e9 P, Fleuret F, Fua P (2017) Deep occlusion reasoning for multi-camera multi-target detection[C]. In: Proceedings of the IEEE International Conference on Computer Vision, p 271\u2013279.","DOI":"10.1109\/ICCV.2017.38"},{"key":"7003_CR17","doi-asserted-by":"publisher","first-page":"2618","DOI":"10.3390\/s21082618","volume":"21","author":"Q Wu","year":"2021","unstructured":"Wu Q, Feng D, Cao C, Zeng X, Feng Z, Wu J, Huang Z (2021) Improved mask R-CNN for aircraft detection in remote sensing images. Sensors 21:2618","journal-title":"Sensors"},{"issue":"4","key":"7003_CR18","doi-asserted-by":"publisher","first-page":"984","DOI":"10.3390\/rs14040984","volume":"14","author":"Q Li","year":"2022","unstructured":"Li Q, Chen Y, Zeng Y (2022) Transformer with transfer CNN for remote-sensing-image object detection[J]. Remote Sens 14(4):984","journal-title":"Remote Sens"},{"issue":"1","key":"7003_CR19","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1109\/TCYB.2022.3162945","volume":"53","author":"G Li","year":"2022","unstructured":"Li G, Liu Z, Zeng D et al (2022) Adjacent context coordination network for salient object detection in optical remote sensing images[J]. IEEE Trans Cybern 53(1):526\u2013538","journal-title":"IEEE Trans Cybern"},{"key":"7003_CR20","doi-asserted-by":"publisher","first-page":"2616","DOI":"10.3390\/rs15102616","volume":"15","author":"W Wang","year":"2023","unstructured":"Wang W, Shi Y, Zhang J, Hu L, Li S, He D, Liu F (2023) Traditional village building extraction based on improved mask R-CNN: a case study of Beijing. China Remote Sens 15:2616","journal-title":"China Remote Sens"},{"issue":"8","key":"7003_CR21","doi-asserted-by":"publisher","first-page":"1971","DOI":"10.3390\/rs15081971","volume":"15","author":"R Niu","year":"2023","unstructured":"Niu R, Zhi X, Jiang S et al (2023) Aircraft target detection in low signal-to-noise ratio visible remote sensing images[J]. Remote Sens 15(8):1971","journal-title":"Remote Sens"},{"issue":"14","key":"7003_CR22","doi-asserted-by":"publisher","first-page":"6414","DOI":"10.3390\/s23146414","volume":"23","author":"Z Li","year":"2023","unstructured":"Li Z, Yuan J, Li G et al (2023) RSI-YOLO: object detection method for remote sensing images based on improved YOLO[J]. Sensors 23(14):6414","journal-title":"Sensors"},{"key":"7003_CR23","doi-asserted-by":"crossref","unstructured":"Wang L, Shoulin Y, Alyami H, et al (2022) A novel deep learning\u2010based single shot multibox detector model for object detection in optical remote sensing images[J]","DOI":"10.1002\/gdj3.162"},{"key":"7003_CR24","doi-asserted-by":"crossref","unstructured":"Chefer H, Gur S, Wolf L (2021) Transformer interpretability beyond attention visualization[C]. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, p 782\u2013791","DOI":"10.1109\/CVPR46437.2021.00084"},{"key":"7003_CR25","doi-asserted-by":"publisher","first-page":"105285","DOI":"10.1016\/j.envsoft.2021.105285","volume":"148","author":"RJ Pally","year":"2022","unstructured":"Pally RJ, Samadi S (2022) Application of image processing and convolutional neural networks for flood image classification and semantic segmentation[J]. Environ Model Softw 148:105285","journal-title":"Environ Model Softw"},{"key":"7003_CR26","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1016\/j.neucom.2021.04.038","volume":"454","author":"J Li","year":"2021","unstructured":"Li J, Wang X, Tu Z et al (2021) On the diversity of multi-head attention[J]. Neurocomputing 454:14\u201324","journal-title":"Neurocomputing"},{"issue":"3","key":"7003_CR27","doi-asserted-by":"publisher","first-page":"79","DOI":"10.3390\/aerospace8030079","volume":"8","author":"CJ Swinney","year":"2021","unstructured":"Swinney CJ, Woods JC (2021) Unmanned aerial vehicle operating mode classification using deep residual learning feature extraction[J]. Aerospace 8(3):79","journal-title":"Aerospace"},{"key":"7003_CR28","doi-asserted-by":"crossref","unstructured":"Wang CY, Liao HYM, Wu YH, et al (2020) CSPNet: a new backbone that can enhance learning capability of CNN[C]. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, p 390\u2013391","DOI":"10.1109\/CVPRW50498.2020.00203"},{"key":"7003_CR29","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1016\/S1571-0661(05)82552-6","volume":"15","author":"P Borovansk\u00fd","year":"1998","unstructured":"Borovansk\u00fd P, Kirchner C, Kirchner H et al (1998) An overview of ELAN[J]. Electron Notes Theor Comput Sci 15:55\u201370","journal-title":"Electron Notes Theor Comput Sci"},{"key":"7003_CR30","doi-asserted-by":"crossref","unstructured":"O\u2019Connor L (1994) On the distribution of characteristics in bijective mappings[C]. Advances in Cryptology\u2014EUROCRYPT\u201993: Workshop on the Theory and Application of Cryptographic Techniques Lofthus, Norway, May 23\u201327, 1993 Proceedings 12. Springer Berlin Heidelberg,p 360-370","DOI":"10.1007\/3-540-48285-7_31"},{"key":"7003_CR31","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.isprsjprs.2016.03.014","volume":"117","author":"G Cheng","year":"2016","unstructured":"Cheng G, Han J (2016) A survey on object detection in optical remote sensing images[J]. ISPRS J Photogramm Remote Sens 117:11\u201328","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"7003_CR32","unstructured":"Redmon J, Farhadi A (2018) Yolov3: an incremental improvement[J]. arXiv preprint arXiv:1804.02767"},{"issue":"14","key":"7003_CR33","doi-asserted-by":"publisher","first-page":"1711","DOI":"10.3390\/electronics10141711","volume":"10","author":"J Yao","year":"2021","unstructured":"Yao J, Qi J, Zhang J et al (2021) A real-time detection algorithm for kiwifruit defects based on YOLOv5[J]. Electronics 10(14):1711","journal-title":"Electronics"},{"key":"7003_CR34","doi-asserted-by":"crossref","unstructured":"Wang CY, Bochkovskiy A, Liao HYM (2023) YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors[C]. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 7464\u20137475","DOI":"10.1109\/CVPR52729.2023.00721"},{"key":"7003_CR35","doi-asserted-by":"crossref","unstructured":"Sohan M, Sai Ram T, Reddy R, et al (2024) A review on YOLOv8 and its advancements[C]. In: International Conference on Data Intelligence and Cognitive Informatics. Springer, Singapore, p 529\u2013545","DOI":"10.1007\/978-981-99-7962-2_39"},{"key":"7003_CR36","unstructured":"Ren S, He K, Girshick R, et al (2015) Faster r-cnn: towards real-time object detection with region proposal networks[J]. Advances in neural information processing systems 28"},{"key":"7003_CR37","doi-asserted-by":"crossref","unstructured":"Cai Z, Vasconcelos N (2018) Cascade r-cnn: delving into high quality object detection[C]. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, p 6154\u20136162","DOI":"10.1109\/CVPR.2018.00644"},{"key":"7003_CR38","doi-asserted-by":"crossref","unstructured":"Gao T, Liu Z, Zhang J, et al (2023) A task-balanced multi-scale adaptive fusion network for object detection in remote sensing images[J]. IEEE Transactions on Geoscience and Remote Sensing","DOI":"10.1109\/TGRS.2023.3289878"},{"issue":"10","key":"7003_CR39","doi-asserted-by":"publisher","first-page":"4997","DOI":"10.3390\/app12104997","volume":"12","author":"Y Sun","year":"2022","unstructured":"Sun Y, Liu W, Gao Y et al (2022) A dense feature pyramid network for remote sensing object detection[J]. Appl Sci 12(10):4997","journal-title":"Appl Sci"},{"issue":"5","key":"7003_CR40","doi-asserted-by":"publisher","first-page":"862","DOI":"10.3390\/rs13050862","volume":"13","author":"Z Yuan","year":"2021","unstructured":"Yuan Z, Liu Z, Zhu C et al (2021) Object detection in remote sensing images via multi-feature pyramid network with receptive field block[J]. Remote Sens 13(5):862","journal-title":"Remote Sens"},{"key":"7003_CR41","doi-asserted-by":"crossref","unstructured":"Gao T, Niu Q, Zhang J, et al (2023) Global to local: a scale-aware network for remote sensing object detection[J]. IEEE Transactions on Geoscience and Remote Sensing","DOI":"10.1109\/TGRS.2023.3294241"},{"issue":"5","key":"7003_CR42","doi-asserted-by":"publisher","first-page":"3377","DOI":"10.1109\/TGRS.2019.2954328","volume":"58","author":"P Wang","year":"2019","unstructured":"Wang P, Sun X, Diao W et al (2019) FMSSD: feature-merged single-shot detection for multiscale objects in large-scale remote sensing imagery[J]. IEEE Trans Geosci Remote Sens 58(5):3377\u20133390","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"2","key":"7003_CR43","doi-asserted-by":"publisher","first-page":"427","DOI":"10.3390\/rs14020427","volume":"14","author":"J Liu","year":"2022","unstructured":"Liu J, Yang D, Hu F (2022) Multiscale object detection in remote sensing images combined with multi-receptive-field features and relation-connected attention[J]. Remote Sens 14(2):427","journal-title":"Remote Sens"},{"key":"7003_CR44","first-page":"1","volume":"60","author":"S Tian","year":"2021","unstructured":"Tian S, Kang L, Xing X et al (2021) A relation-augmented embedded graph attention network for remote sensing object detection[J]. IEEE Trans Geosci Remote Sens 60:1\u201318","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"7003_CR45","first-page":"1","volume":"60","author":"Y Liu","year":"2021","unstructured":"Liu Y et al (2021) ABNet: adaptive balanced network for multiscale object detection in remote sensing imagery. IEEE Trans Geosci Remote Sens 60:1\u201314","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"6","key":"7003_CR46","doi-asserted-by":"publisher","first-page":"1002","DOI":"10.3390\/rs16061002","volume":"16","author":"D Zhao","year":"2024","unstructured":"Zhao D, Shao F, Liu Q et al (2024) A small object detection method for drone-captured images based on improved YOLOv7[J]. Remote Sens 16(6):1002","journal-title":"Remote Sens"},{"key":"7003_CR47","unstructured":"Han QGHHZ, Li QFY (2024) GLFE-YOLOX: global and local feature enhanced YOLOX for remote sensing images[J]"},{"key":"7003_CR48","doi-asserted-by":"crossref","unstructured":"Duan K et al (2019) Centernet: keypoint triplets for object detection. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision","DOI":"10.1109\/ICCV.2019.00667"},{"key":"7003_CR49","doi-asserted-by":"crossref","unstructured":"Liu W, Anguelov D, Erhan D, et al (2016) Ssd: single shot multibox detector[C]. In: Computer Vision\u2013ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11\u201314, 2016, Proceedings, Part I 14. Springer International Publishing, p 21\u201337","DOI":"10.1007\/978-3-319-46448-0_2"},{"key":"7003_CR50","unstructured":"Li C, Zhou A, Yao A (2022) Omni-dimensional dynamic convolution. arXiv preprint arXiv:2209.07947"},{"key":"7003_CR51","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.isprsjprs.2014.10.002","volume":"98","author":"G Cheng","year":"2014","unstructured":"Cheng G et al (2014) Multi-class geospatial object detection and geographic image classification based on collection of part detectors. ISPRS J Photogramm Remote Sens 98:119\u2013132","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"7003_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s40537-016-0043-6","volume":"3","author":"K Weiss","year":"2016","unstructured":"Weiss K, Khoshgoftaar TM, Wang DD (2016) A survey of transfer learning[J]. J Big Data 3:1\u201340","journal-title":"J Big Data"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07003-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-025-07003-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-025-07003-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T08:44:41Z","timestamp":1740473081000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-025-07003-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,24]]},"references-count":52,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2025,3]]}},"alternative-id":["7003"],"URL":"https:\/\/doi.org\/10.1007\/s11227-025-07003-5","relation":{},"ISSN":["1573-0484"],"issn-type":[{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,24]]},"assertion":[{"value":"28 January 2025","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 February 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":"All authors disclosed no relevant relationships.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"542"}}