{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T08:25:37Z","timestamp":1773735937551,"version":"3.50.1"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"21","license":[{"start":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T00:00:00Z","timestamp":1704153600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T00:00:00Z","timestamp":1704153600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation","doi-asserted-by":"crossref","award":["61877051"],"award-info":[{"award-number":["61877051"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61170192"],"award-info":[{"award-number":["61170192"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-17957-4","type":"journal-article","created":{"date-parts":[[2024,1,2]],"date-time":"2024-01-02T08:02:46Z","timestamp":1704182566000},"page":"61007-61023","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["The improved YOLOv8 algorithm based on EMSPConv and SPE-head modules"],"prefix":"10.1007","volume":"83","author":[{"given":"Guihao","family":"Wen","sequence":"first","affiliation":[]},{"given":"Ming","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yonghang","family":"Luo","sequence":"additional","affiliation":[]},{"given":"Chaoshan","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Yunfei","family":"Tan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,1,2]]},"reference":[{"key":"17957_CR1","volume-title":"2023 International Wireless Communications and Mobile Computing (IWCMC)","author":"H Orchi","year":"2023","unstructured":"Orchi H, Sadik M, Khaldoun M, Sabir E (2023) Real-time detection of crop leaf diseases using enhanced YOLOv8 algorithm. In: 2023 International Wireless Communications and Mobile Computing (IWCMC). Marrakesh, Morocco 1690\u20131696"},{"key":"17957_CR2","unstructured":"Terven J, Cordova-Esparza D (2023) A comprehensive review of YOLO: From YOLOv1 to YOLOv8 and beyond. arXiv preprint arXiv:2304.00501"},{"key":"17957_CR3","doi-asserted-by":"publisher","unstructured":"Bhosale YH, Zanwar SR, Ali SS, Vaidya NS, Auti RA, Patil DH (2023) Multi-plant and multi-crop leaf disease detection and classification using deep neural networks, machine learning, image processing with precision agriculture - A review. In: 2023 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, pp 1\u20137. https:\/\/doi.org\/10.1109\/ICCCI56745.2023.10128246","DOI":"10.1109\/ICCCI56745.2023.10128246"},{"issue":"5","key":"17957_CR4","doi-asserted-by":"publisher","first-page":"304","DOI":"10.3390\/drones7050304","volume":"7","author":"Y Li","year":"2023","unstructured":"Li Y, Fan Q, Huang H, Han Z, Gu Q (2023) a modified yolov8 detection network for UAV aerial image recognition. Drones 7(5):304","journal-title":"Drones"},{"key":"17957_CR5","doi-asserted-by":"publisher","first-page":"898","DOI":"10.3389\/fpls.2020.00898","volume":"11","author":"J Liu","year":"2020","unstructured":"Liu J, Wang X (2020) Tomato diseases and pests detection based on improved yolo v3 convolutional neural network. Front Plant Sci 11:898","journal-title":"Front Plant Sci"},{"key":"17957_CR6","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1016\/j.biosystemseng.2021.11.011","volume":"212","author":"H Li","year":"2021","unstructured":"Li H, Li C, Li G, Chen L (2021) A real-time table grape detection method based on improved yolov4-tiny network in complex back-ground. Biosys Eng 212:347\u2013359","journal-title":"Biosys Eng"},{"issue":"3","key":"17957_CR7","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1007\/s11760-021-02024-y","volume":"16","author":"MP Mathew","year":"2022","unstructured":"Mathew MP, Mahesh TY (2022) Leaf-based disease detection in bell pepper plant using yolo v5. Signal Image Video Process 16(3):841\u2013847. https:\/\/doi.org\/10.1007\/s11760-021-02024-y","journal-title":"Signal Image Video Process"},{"key":"17957_CR8","doi-asserted-by":"publisher","first-page":"709","DOI":"10.1007\/978-3-031-19827-4_41","volume-title":"European conference on computer vision","author":"M Jia","year":"2022","unstructured":"Jia M, Tang L, Chen BC, Cardie C, Belongie S, Hariharan B, Lim SN (2022) Visual prompt tuning. In: European conference on computer vision, vol 13693. LNCS, pp 709\u2013727. https:\/\/doi.org\/10.1007\/978-3-031-19827-4_41"},{"key":"17957_CR9","doi-asserted-by":"crossref","unstructured":"Han C, Wang Q, Cui Y, Cao Z, Wang W, Qi S, Liu D (2023) E2VPT: An effective and efficient approach for visual prompt tuning. arXiv preprint arXiv:2307.13770","DOI":"10.1109\/ICCV51070.2023.01604"},{"key":"17957_CR10","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai","volume-title":"Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI). International Joint Conferences on Artificial Intelligence Organization","author":"L Yan","year":"2023","unstructured":"Yan L, Han C, Xu Z, Liu D, Wang Q (2023) Prompt learns prompt: exploring knowledge-aware generative prompt collaboration for video captioning. In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence (IJCAI). International Joint Conferences on Artificial Intelligence Organization, vol 180. https:\/\/doi.org\/10.24963\/ijcai"},{"key":"17957_CR11","doi-asserted-by":"publisher","first-page":"9041","DOI":"10.1109\/CVPR.2019.00926","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"X Wang","year":"2019","unstructured":"Wang X, Kan M, Shan S, Chen X (2019) Fully learnable group convolution for acceleration of deep neural networks. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 9041\u20139050. https:\/\/doi.org\/10.1109\/CVPR.2019.00926"},{"key":"17957_CR12","doi-asserted-by":"publisher","first-page":"4383","DOI":"10.1109\/ICCV.2017.469","volume-title":"Proceedings of the IEEE international conference on computer vision","author":"T Zhang","year":"2017","unstructured":"Zhang T, Qi GJ, Xiao B, Wang J (2017) Interleaved group convolutions. In: Proceedings of the IEEE international conference on computer vision, pp 4383\u20134392. https:\/\/doi.org\/10.1109\/ICCV.2017.469"},{"key":"17957_CR13","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1109\/CVPR42600.2020.00165","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"K Han","year":"2020","unstructured":"Han K, Wang Y, Tian Q, Guo J, Xu C, Xu C (2020) Ghostnet: More features from cheap operations. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 1577\u20131586. https:\/\/doi.org\/10.1109\/CVPR42600.2020.00165"},{"key":"17957_CR14","doi-asserted-by":"publisher","first-page":"2678","DOI":"10.1109\/TIP.2023.3272826","volume":"32","author":"D Liu","year":"2023","unstructured":"Liu D, Liang J, Geng T, Loui A, Zhou T (2023) Tripartite feature enhanced pyramid network for dense prediction. IEEE Trans Image Processing 32:2678\u20132692. https:\/\/doi.org\/10.1109\/TIP.2023.3272826","journal-title":"IEEE Trans Image Processing"},{"key":"17957_CR15","first-page":"6101","volume-title":"Proceedings of the AAAI Conference on Artificial Intelligence","author":"D Liu","year":"2021","unstructured":"Liu D, Cui Y, Yan L, Mousas C, Yang B, Chen Y (2021) Densernet: Weakly supervised visual localization using multi-scale feature aggregation. In Proceedings of the AAAI Conference on Artificial Intelligence 35(7):6101\u20136109"},{"key":"17957_CR16","doi-asserted-by":"publisher","first-page":"9811","DOI":"10.1109\/CVPR46437.2021.00969","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","author":"D Liu","year":"2021","unstructured":"Liu D, Cui Y, Tan W, Chen Y (2021) Sg-net: Spatial granularity network for one-stage video instance segmentation. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 9811\u20139820. https:\/\/doi.org\/10.1109\/CVPR46437.2021.00969"},{"key":"17957_CR17","unstructured":"Li H, Li J, Wei H, Liu Z, Zhan Z, Ren Q (2022) Slim-neck by GSConv: A better design paradigm of detector architectures for autonomous vehicles. arXiv preprint arXiv:2206.02424"},{"key":"17957_CR18","first-page":"4375","volume":"6","author":"T Cohen","year":"2016","unstructured":"Cohen T, Welling M (2016) Group equivariant convolutional networks. In International conference on machine learning ICML 6:4375\u20134386","journal-title":"In International conference on machine learning ICML"},{"key":"17957_CR19","doi-asserted-by":"publisher","first-page":"7369","DOI":"10.1109\/CVPR46437.2021.00729","volume-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","author":"X Dai","year":"2021","unstructured":"Dai X, Chen Y, Xiao B, Chen D, Liu M, Yuan L, Zhang L (2021) Dynamic head: Unifying object detection heads with attentions. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 7369\u20137378. https:\/\/doi.org\/10.1109\/CVPR46437.2021.00729"},{"issue":"5","key":"17957_CR20","doi-asserted-by":"publisher","first-page":"1113","DOI":"10.1088\/0031-9155\/51\/5\/004","volume":"51","author":"S Moehrs","year":"2006","unstructured":"Moehrs S, Del Guerra A, Herbert DJ, Mandelkern MA (2006) A detector head design for small-animal PET with silicon photomultipliers (SiPM). Phys Med Biol 51(5):1113","journal-title":"Phys Med Biol"},{"key":"17957_CR21","doi-asserted-by":"publisher","first-page":"447","DOI":"10.1201\/9781420011579.CH19","volume-title":"Longitudinal data analysis","author":"PS Albert","year":"2008","unstructured":"Albert PS, Follmann DA (2008) Shared-parameter models. In: Longitudinal data analysis. Chapman and Hall\/CR, pp 447\u2013466. https:\/\/doi.org\/10.1201\/9781420011579.CH19"},{"key":"17957_CR22","doi-asserted-by":"publisher","first-page":"5350","DOI":"10.1109\/CVPRW59228.2023.00564","volume-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops","author":"A Aboah","year":"2023","unstructured":"Aboah A, Wang B, Bagci U, Adu-Gyamfi Y (2023) Real-time multi-class helmet violation detection using few-shot data sampling technique and yolov8. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp 5350\u20135358. https:\/\/doi.org\/10.1109\/CVPRW59228.2023.00564"},{"issue":"28","key":"17957_CR23","doi-asserted-by":"publisher","first-page":"20939","DOI":"10.1007\/s00521-023-08809-1","volume":"35","author":"FM Talaat","year":"2023","unstructured":"Talaat FM, ZainEldin H (2023) An improved fire detection approach based on YOLO-v8 for smart cities. Neural Comput Applications 35(28):20939\u201320954. https:\/\/doi.org\/10.1007\/s00521-023-08809-1","journal-title":"Neural Comput Applications"},{"issue":"10","key":"17957_CR24","doi-asserted-by":"publisher","first-page":"2323","DOI":"10.3390\/electronics12102323","volume":"12","author":"H Lou","year":"2023","unstructured":"Lou H, Duan X, Guo J, Liu H, Gu J, Bi L, Chen H (2023) DC-YOLOv8: Small-size object detection algorithm based on camera sensor. Electronics 12(10):2323","journal-title":"Electronics"},{"issue":"7","key":"17957_CR25","doi-asserted-by":"publisher","first-page":"677","DOI":"10.3390\/machines11070677","volume":"11","author":"M Hussain","year":"2023","unstructured":"Hussain M (2023) YOLO-v1 to YOLO-v8, the rise of YOLO and its complementary nature toward digital manufacturing and industrial defect detection. Machines 11(7):677","journal-title":"Machines"},{"key":"17957_CR26","unstructured":"Wang W, Cheng H, Zhou T et al (2023) Visual recognition with deep nearest centroids. arXiv:2209.07383 [cs.CV]"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17957-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-17957-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-17957-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,4]],"date-time":"2024-06-04T04:08:27Z","timestamp":1717474107000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-17957-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,2]]},"references-count":26,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2024,6]]}},"alternative-id":["17957"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-17957-4","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,2]]},"assertion":[{"value":"20 September 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 December 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 January 2024","order":4,"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 that they do not have any conflicts of interest that influence the work reported in this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No animals were involved in this study. All applicable international, national, and\/or institutional guidelines for the care and use of animals were followed.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}