article
Efficient waste management and resource recovery hinge on precise waste sorting. This paper introduces an upgraded waste sorting methodology utilizing convolutional neural networks (CNNs) and transfer learning, specifically employing VGG16 architectures. The presented approach seeks to enhance accuracy, efficiency, and adaptability in practical waste sorting scenarios.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1109/mscc62288.2024.10697050
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
