Traditional Chinese Medicine Recognition Based on Target Detection

Abstract

Traditional Chinese medicine (TCM) is widely used in China, but the large variety can easily lead to difficulties in visual identification. This study aims to evaluate the availability of target detection models to identify TCMs. We have collected images of 100 common TCMs in pharmacies, and use three current mainstream target detection models: Faster RCNN, SSD, and YOLO v5 to train the TCM dataset. By comparing the metrics of the three models, the results show that the YOLO v5 model has obvious advantages in the recognition of a variety of TCM, the mean average accuracy of the YOLO v5 is 94.33% and the FPS has reached 75, this model has a smaller number of parameters and solves the problem of detection and occlusion for small targets. Our experiments prove that the target detection technology has broad application prospects in the detection of TCM.

Research on defect recognition method of transmission line insulators

“…YOLO-V5 9 integrates the structures of CSPDarknet53, PANET and SPP, which performs well in object detection, and the reasoning speed of YOLO-V5s model is even faster than 140FPS. In fact, Considering the damage part of the insulator is the focus we care about, we choose the YOLO-V5s model to recognize the type of damage accurately.…”