An Automatic Jujube Fruit Detection and Ripeness Inspection Method in the Natural Environment

The ripeness phases of jujube fruits are one factor mitigating against fruit detection, in addition to uneven environmental conditions such as illumination variation, leaf occlusion, overlapping fruits, colors or brightness, similar plant appearance the background, and so on. Therefore, a method called YOLO-Jujube was proposed solve these problems. With incorporation networks Stem, RCC, Maxpool, CBS, SPPF, C3, PANet, CIoU loss, able detect automatically for inspection. Having recorded params 5.2 m, GFLOPs 11.7, AP 88.8%, speed 245 fps detection performance, including sorting counting process combined, outperformed network YOLOv3-tiny, YOLOv4-tiny, YOLOv5s, YOLOv7-tiny. is robust applicable meet goal computer vision-based understanding images videos.