Medical Waste Classification using Deep Learning and Convolutional Neural Networks
Published in IEEE IATMSI 2022 (IEEE Xplore) — cited 25 times, 2023
First author. Trained a CNN to 98.4% accuracy for medical-waste classification and deployed it as an interactive TensorFlow.js web application. Multi-class classification of medical waste as part of an automated system to segregate it without human intervention. Cited 25 times.
Recommended citation: M. Verma, A. Kumar and S. Kumar, "Medical Waste Classification using Deep Learning and Convolutional Neural Networks," 2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India, 2022, pp. 1-5, doi: 10.1109/IATMSI56455.2022.10119431. keywords: {Training;Deep learning;Computer vision;Technological innovation;Hospitals;Computational modeling;Transfer learning;Deep Learning;Medical Waste Classification;Transfer Learning;Convolutional Neural Network(CNN)},
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