and reduce post-harvest losses. This study provides new ideas and technical references for the application of machine vision technology in the field of dense crop maturity recognition. Keywords : object detection，因此识别采摘和运输过程中的颜色变化至关重要， 2026; 19(1): 295–301. Dense strawberry maturity recognition neural network based on multichannel attention mechanism Zhaorui Cao 1 ，具有良好的识别准确性和稳定性， China) Abstract : Color is an important indicator of strawberry maturity; therefore， feature fusion。
中国； 2. 渤海大学食品科学与工程学院， compared to the original YOLOv8s model，辛晓杰 1 ， Bohai University， Shenyang 110159，该研究提出了一种基于 YOLOv8s 的密集草莓成熟度识别卷积神经网络， 1.8%， Liaoning，沈阳110159， 尽管学者们在利用机器视觉技术进行作物检测方面取得了显著进展， Cai J H. Dense strawberry maturity recognition neural network based on multichannel attention mechanism. Int J Agric Biol Eng，以及在密集放置的草莓中难以区分单个水果的问题 ， 1.2%， fuzzy maturity criteria， including the overlapping of adjacent fruit features，才佳卉 2* ( 1. 沈阳理工大学装备工程学院， it optimizes the convergence effect and inference accuracy of network training. On a custom strawberry dataset，该网络集成了多尺度特征注意力机制， deep learning DOI : 10.25165/j.ijabe.20261901. 9931