Apple Detection with Occlusions Using Modified YOLOv5-v1
IEEE IDAACS 2023
Abstract
This paper presents a modified YOLOv5-v1 architecture optimized for detecting apples with occlusions in orchard environments. The model achieves improved accuracy for partially visible fruits, enabling more reliable fruit counting for precision agriculture applications.
Citation
Oleksandr Melnychenko, Oleg Savenko, Pavlo Radiuk. "Apple Detection with Occlusions Using Modified YOLOv5-v1". IEEE IDAACS 2023, 2023.