Intact Detection of Highly Occluded Immature Tomatoes on Plants Using Deep Learning Techniques.

ABSTRACT: Automatic detection of intact tomatoes on plants is highly expected for low-cost and optimal management in tomato farming. Mature tomato detection has been wildly studied, while immature tomato detection, especially when occluded with leaves, is difficult to perform using traditional image analysis, which is more important for long-term yield prediction. Therefore, tomato detection that can generalize well in real tomato cultivation scenes and is robust to issues such as fruit occlusion and variable lighting conditions is highly desired. In this study, we build a tomato detection model to automatically detect intact green tomatoes regardless of occlusions or fruit growth stage using deep learning approaches. The tomato detection model used faster region-based convolutional neural network (

SUBMITTER: Mu Y 

PROVIDER: S-EPMC7288109 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature