TY - GEN
T1 - Medical Waste Detection and Classification Through YOLO Algorithms
AU - Moktar, Muhammad H.Bin
AU - Hajjaj, Sami Salama Hussen
AU - Mohamed, Hassan
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - General waste is commonly managed to reduce pollution. Similarly, medical waste can be classified and managed to not only reduce pollution but also mitigate health risks and accidental injuries. Medical waste includes a variety of materials such as those contaminated with body fluids, sharps waste, and chemical waste. This study evaluates modern Artificial Intelligence methods for classifying medical waste such as facemasks, gloves, and syringes. Various classification models, including CNN, ResNet50, YOLO v3, and YOLO v4, were used and compared. YOLO v4 achieves a higher mAP (89.21%), surpassing YOLO v3 and other YOLO models used in waste classification studies. YOLO v4 was then tested in object detection and successfully identified masks, gloves, and syringes. Further performance evaluations are necessary to enhance the detection of medical waste and other objects in various applications.
AB - General waste is commonly managed to reduce pollution. Similarly, medical waste can be classified and managed to not only reduce pollution but also mitigate health risks and accidental injuries. Medical waste includes a variety of materials such as those contaminated with body fluids, sharps waste, and chemical waste. This study evaluates modern Artificial Intelligence methods for classifying medical waste such as facemasks, gloves, and syringes. Various classification models, including CNN, ResNet50, YOLO v3, and YOLO v4, were used and compared. YOLO v4 achieves a higher mAP (89.21%), surpassing YOLO v3 and other YOLO models used in waste classification studies. YOLO v4 was then tested in object detection and successfully identified masks, gloves, and syringes. Further performance evaluations are necessary to enhance the detection of medical waste and other objects in various applications.
KW - Artificial Intelligence
KW - Deep Learning
KW - Machine Learning
UR - http://www.scopus.com/inward/record.url?scp=85211356838&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-70687-5_3
DO - 10.1007/978-3-031-70687-5_3
M3 - Conference Proceeding
AN - SCOPUS:85211356838
SN - 9783031706868
T3 - Lecture Notes in Networks and Systems
SP - 22
EP - 33
BT - Robot Intelligence Technology and Applications 8 - Results from the 11th International Conference on Robot Intelligence Technology and Applications
A2 - Abdul Majeed, Anwar P. P.
A2 - Yap, Eng Hwa
A2 - Liu, Pengcheng
A2 - Huang, Xiaowei
A2 - Nguyen, Anh
A2 - Chen, Wei
A2 - Kim, Ue-Hwan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 11th International Conference on Robot Intelligence Technology and Applications, RiTA 2023
Y2 - 6 December 2023 through 8 December 2023
ER -
