ArticleAnimals : an open access journal from MDPI2025
YOLOv8A-SD: A Segmentation-Detection Algorithm for Overlooking Scenes in Pig Farms.
Article in Animals : an open access journal from MDPI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- VM-RTDETR: Advancing DETR with Vision State-Space Duality and Multi-Scale Fusion for Robust Pig Detection.Animals : an open access journal from MDPI · 2025Article
- Weed Segmentation in Soybean Fields and Variable-Rate Herbicide Prescription Map Generation Based on UAV Imagery and Improved YOLOv11-seg Model.Frontiers in plant science · 2025Article
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Authors and funding
8 authors.
Funding
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Abstract
A refined YOLOv8A-SD model is introduced to address pig detection challenges in aerial surveillance of pig farms. The model incorporates the ADown attention mechanism and a dual-task strategy combining detection and segmentation tasks. Testing was conducted using top-view footage from a large-scale pig farm in Sichuan, with 924 images for detection training, 216 for validation, and 2985 images for segmentation training, with 1512 for validation. The model achieved 96.1% Precision and 96.3% mAP50 in detection tasks while maintaining strong segmentation performance (IoU: 83.1%). A key finding reveals that training with original images while applying segmentation preprocessing during testing provides optimal results, achieving exceptional counting accuracy (25.05 vs. actual 25.09 pigs) and simplifying practical deployment. The research demonstrates YOLOv8A-SD's effectiveness in complex farming environments, providing reliable monitoring capabilities for intelligent farm management applications.
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Registered trials
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