{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:10:44Z","timestamp":1763341844307,"version":"3.45.0"},"reference-count":22,"publisher":"Tech Science Press","issue":"2","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063270","type":"journal-article","created":{"date-parts":[[2025,4,16]],"date-time":"2025-04-16T02:58:11Z","timestamp":1744772291000},"page":"2323-2349","source":"Crossref","is-referenced-by-count":0,"title":["Improving Hornet Detection with the YOLOv7-Tiny Model: A Case Study on Asian Hornets"],"prefix":"10.32604","volume":"83","author":[{"given":"Yung-Hsiang","family":"Hung","sequence":"first","affiliation":[]},{"given":"Chuen-Kai","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Wen-Pai","family":"Wang","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1098\/rspb.2006.3721","article-title":"Importance of pollinators in changing landscapes for world crops","volume":"274","author":"Klein","year":"2007","journal-title":"Proc R Soc B"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"e37235","DOI":"10.1371\/journal.pone.0037235","article-title":"Insect pollinated crops, insect pollinators and US agriculture: trend analysis of aggregate data for the period 1992\u20132009","volume":"7","author":"Calderone","year":"2012","journal-title":"PLoS One"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"e0242668","DOI":"10.1371\/journal.pone.0242668","volume":"15","author":"Mattila","year":"2020","journal-title":"PLoS One"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1126\/science.aaa8415","article-title":"Machine learning: trends, perspectives, and prospects","volume":"349","author":"Jordan","year":"2015","journal-title":"Science"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1186\/s40537-021-00444-8","article-title":"Review of deep learning: concepts, CNN architectures, challenges, applications, future directions","volume":"8","author":"Alzubaidi","year":"2021","journal-title":"J Big Data"},{"key":"ref7","unstructured":"Terven J, Cordova D. A comprehensive review of YOLO: from YOLOv1 to YOLOv8 and beyond. arXiv:2304.00501. 2023. doi:10.48550\/arXiv.2304.00501."},{"key":"ref8","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"779","article-title":"You only look once: unified, real-time object detection","author":"Redmon","year":"2016 Jun 27\u201330"},{"key":"ref9","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"7263","article-title":"YOLO9000: better, faster, stronger","author":"Redmon","year":"2017 Jul 21\u201326"},{"key":"ref10","unstructured":"Redmon J, Farhadi A. YOLOv3: an incremental improvement. arXiv.1804.02767. 2018. doi: 10.48550\/arXiv.1804.02767."},{"key":"ref11","unstructured":"Bochkovskiy A, Wang CY, Liao HYM. YOLOv4: optimal speed and accuracy of object detection. arXiv.2004.10934. 2020. doi:10.48550\/arXiv.2004.10934."},{"key":"ref12","first-page":"17","article-title":"YOLOv7 performance comparison: a survey","volume":"12","author":"Gillani","year":"2022","journal-title":"Comput Sci Inf Technol"},{"key":"ref13","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","first-page":"7464","article-title":"YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors","author":"Wang","year":"2023 Jun 18\u201322"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.procs.2018.05.198","article-title":"An analysis of convolutional neural networks for image classification","volume":"132","author":"Sharma","year":"2018","journal-title":"Procedia Comput Sci"},{"key":"ref15","series-title":"Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD)","first-page":"443","article-title":"No more strided convolutions or pooling: a new CNN building block for low-resolution images and small objects","author":"Sunkara","year":"2022 Sep 19\u201323"},{"key":"ref16","first-page":"7132","article-title":"Squeeze-and-excitation networks","author":"Hu","year":"2018","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"2011","DOI":"10.1109\/TPAMI.2019.2913372","article-title":"Squeeze-and-excitation networks","volume":"42","author":"Hu","year":"2020","journal-title":"IEEE Trans. Pattern Ana. Mach Intell"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"106268","DOI":"10.1016\/j.cmpb.2021.106268","article-title":"SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling-based residual U-Net for automatic liver segmentation in computed tomography","volume":"208","author":"Wang","year":"2021","journal-title":"Comput Methods Programs Biomed"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"108490","DOI":"10.1016\/j.compeleceng.2022.108490","article-title":"An improved algorithm for small object detection based on YOLO v4 and multi-scale contextual information","volume":"105","author":"Ji","year":"2023","journal-title":"Comput Electr Eng"},{"key":"ref20","unstructured":"Project-vrljw, hornet_only dataset, roboflow universe, roboflow [Internet]. 2023 [cited 2025 Mar 12]. Available from: https:\/\/universe.roboflow.com\/project-vrljw\/hornet_only."},{"key":"ref21","unstructured":"Bees and hornets, bees dataset, roboflow universe [Internet]. 2023 [cited 2025 Mar 12]. Available from: https:\/\/universe.roboflow.com\/bees-and-hornets-20yku\/bees-twjei."},{"key":"ref22","unstructured":"Si gn, insect_detection dataset, roboflow universe [Internet]. 2023 [cited 2025 Mar 12]. Available from: https:\/\/universe.roboflow.com\/si-gn\/insect_detection-qsh9u."}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-83-2\/TSP_CMC_63270\/TSP_CMC_63270.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:07:48Z","timestamp":1763341668000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v83n2\/60597"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":22,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063270","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]}}}