Artificial Intelligence Development and Accuracy Evaluation for Green Soybean Appearance Quality Sorting Using Deep Learning (Part 2)

—Effects of Differences in Green Soybean Varieties Included in Datasets on Accuracy of Object Detection AI—

Abstract

For this study, after developing an object detection AI for appearance quality sorting of green soybeans, we investigated the effects on AI accuracy of different green soybean varieties in datasets and different object detection algorithms. After setting seven datasets by combining three varieties, we used these datasets to develop AI for YOLOv3 and Faster R-CNN. Results show that the Precision, Recall, and F-value of the AI, including images of the green soybean varieties to be sorted, were significantly higher. The Newton efficiency (η) of the AI with highest accuracy was 0.79. The contents and percentages of the green soybeans which were misclassified and undetected for appearance quality by AI were different for each object detection algorithm.