Intelligent medical waste detection and classification system based on machine vision

Zhaoxin Cai; Tianhu Bian; Chunyu Bai; Pengxu Li; Changping Sun

doi:10.1117/12.2681166

8 June 2023 Intelligent medical waste detection and classification system based on machine vision

Zhaoxin Cai, Tianhu Bian, Chunyu Bai, Pengxu Li, Changping Sun

Proceedings Volume 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023); 127070N (2023) https://doi.org/10.1117/12.2681166
Event: International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 2023, Changsha, China

Abstract

Since the global eruption of COVID-19, there have been issues with the global medical management system. The classification and treatment of medical waste has brought a huge burden to medical staff. Traditional manual classification has problems such as the heavy workload, difficult identification, and susceptibility to infection. This paper designs an intelligent medical waste detection and classification system based on machine vision. Based on deep learning models such as YOLOv5 and YOLO-resnet18, the data is trained and optimized to obtain a target detection model suitable for medical waste. Through experimental tests, the system has fast detection speed and high accuracy, and the accuracy of medical waste detection and classification reaches 90% and 99% respectively.

Citation Download Citation

Zhaoxin Cai, Tianhu Bian, Chunyu Bai, Pengxu Li, and Changping Sun "Intelligent medical waste detection and classification system based on machine vision", Proc. SPIE 12707, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023), 127070N (8 June 2023); https://doi.org/10.1117/12.2681166

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KEYWORDS

Education and training

Data modeling

Classification systems

Object detection

Visualization

Medical imaging

Visual process modeling

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