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Xingdong Sun, Yukai Zheng, Delin Wu and Yuhang Sui
The key technology of automated apple harvesting is detecting apples quickly and accurately. The traditional detection methods of apple detection are often slow and inaccurate in unstructured orchards. Therefore, this article proposes an improved YOLOv5s...
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Lei Yang, Dexu Mu, Zhen Xu and Kaiyu Huang
Aiming at the problems of uneven light reflectivity on the spherical surface and high similarity between the stems/calyxes and scars that exist in the detection of surface defects in apples, this paper proposed a defect detection method based on image se...
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Mohd Asyraf Zulkifley, Asraf Mohamed Moubark, Adhi Harmoko Saputro and Siti Raihanah Abdani
Apples are one of the most consumed fruits, and they require efficient harvesting procedures to remains in optimal states for a longer period, especially during transportation. Therefore, automation has been adopted by many orchard operators to help in t...
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