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  4. Particle Size Estimation in Mixed Commercial Waste Images Using Deep Learning
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Particle Size Estimation in Mixed Commercial Waste Images Using Deep Learning

Author(s)
Kittiworapanya, Phongsathorn
Pasupa, Kitsuchart
Auer, Peter
Date Issued
June 29, 2021
Type
Conference Paper
DOI
10.1145/3468784.3471273
Abstract
We assessed several state-of-the-art deep learning algorithms and computer vision techniques for estimating the particle size of mixed commercial waste from images. In waste management, the first step is often coarse shredding, using the particle size to set up the shredder machine. The difficulty is separating the waste particles in an image, which can not be performed well. This work focused on estimating size by using the texture from the input image, captured at a fixed height from the camera lens to the ground. We found that EfficientNet achieved the best performance of 0.72 on F1-Score and 75.89% on accuracy.
Citation
ACM International Conference Proceeding Series, 2021
Subjects

Computer Vision

Deep Learning

Mixed Commercial Wast...

Size Estimation

Waste Management

Metrics
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