YOLOv8-SIEMF: A Sub-model Integrated Evaluation and Multi-objective Filtering Approach for Visual Sensing in Telecom Networks

YOLOv8-SIEMF: A Sub-model Integrated Evaluation and Multi-objective Filtering Approach for Visual Sensing in Telecom Networks | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 18 April 2025 V1 Latest version Share on YOLOv8-SIEMF: A Sub-model Integrated Evaluation and Multi-objective Filtering Approach for Visual Sensing in Telecom Networks Authors : Donghao Cao 0009-0008-2127-0639 [email protected] , Fuchen Huang , Zhengxuan Wei , Jingyi Zhu , and Jingsi Lyu Authors Info & Affiliations https://doi.org/10.22541/au.174497607.72628519/v1 213 views 90 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract To address the challenges of missed detection and misdetection in tea bud recognition tasks under complex environments, this paper proposes YOLOv8-SIEMF, a novel detection model integrating Sub-models Integral Evaluation (SIE) and Multi-objective Filtering (MF). First, we design a hierarchical detection framework where different sub-models process diverse resolution levels of input images to extract complementary features. An evaluation mechanism is developed to comprehensively fuse the outputs of sub-models by considering detection confidence, box overlap, and image sharpness. Meanwhile, a multi-objective filtering module is introduced to enhance the model’s sensitivity to multi-target clusters and improve edge sharpness in grayscale space, which effectively reduces redundant or invalid detection. Experimental results on a self-built dataset demonstrate that the proposed model outperforms mainstream YOLOv8 variants in terms of precision and recall, achieving superior performance in recognizing fine-grained tea buds under real-field conditions. Supplementary Material File (yolov8-siemf a sub-model integrated evaluation and multi-objective filtering approach for visual sensing in telecom networks.docx) Download 1.05 MB Information & Authors Information Version history V1 Version 1 18 April 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords edge enhancement multi-objective filter smart agriculture sub-models integral evaluation tea bud detection yolov8 Authors Affiliations Donghao Cao 0009-0008-2127-0639 [email protected] Beijing University of Chemical Technology College of International Education View all articles by this author Fuchen Huang Beijing University of Chemical Technology College of International Education View all articles by this author Zhengxuan Wei Beijing University of Chemical Technology College of Information Science and Technology View all articles by this author Jingyi Zhu Beijing University of Chemical Technology College of International Education View all articles by this author Jingsi Lyu Beijing University of Chemical Technology College of International Education View all articles by this author Metrics & Citations Metrics Article Usage 213 views 90 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Donghao Cao, Fuchen Huang, Zhengxuan Wei, et al. YOLOv8-SIEMF: A Sub-model Integrated Evaluation and Multi-objective Filtering Approach for Visual Sensing in Telecom Networks. Authorea . 18 April 2025. DOI: https://doi.org/10.22541/au.174497607.72628519/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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