Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 05, 2019 - June 08, 2019
This paper describes methods of recognizing cucumbers for autonomous cropping of their fruits. Cucumber recognition from color images by conventional methods is challenging because their leaves and stems have similar colors to that of fruits to be detected. Therefore, we adopted deep learning methods to recognize them. In particular, we compared two types of deep learning architecture. One is U-Net, a network for semantic segmentation, and the other is YOLO, a network for object detection. As a result of the comparison based on precision and recall, we found that U-Net has a comparable performance to YOLO in terms of cucumber fruit detection.
