YOLOV8 farm tomato detection based on attention mechanism and enhanced feature pyramid network

Maoyu Zhu

doi:10.1117/12.3026796

27 March 2024 YOLOV8 farm tomato detection based on attention mechanism and enhanced feature pyramid network

Maoyu Zhu

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131051O (2024) https://doi.org/10.1117/12.3026796
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

As the global population grows and food demand rises, the efficiency and automation of agricultural production have become one of the important challenges facing the world today. Among many crops, tomatoes occupy an important position in modern agricultural production due to their widespread cultivation and consumption. However, the traditional tomato growing and picking process suffers from inefficiency, high costs, and over-reliance on manpower. In response to these challenges, this article proposes a solution using advanced deep learning technology, which is to apply the YOLOv8_GAM_BiFPN network for tomato target detection.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Maoyu Zhu "YOLOV8 farm tomato detection based on attention mechanism and enhanced feature pyramid network", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131051O (27 March 2024); https://doi.org/10.1117/12.3026796

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