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Multilayer Hybrid Deep-Learning Method for Waste Classification and Recycling.
- Source :
- Computational Intelligence & Neuroscience; 11/1/2018, p1-9, 9p
- Publication Year :
- 2018
-
Abstract
- This study proposes a multilayer hybrid deep-learning system (MHS) to automatically sort waste disposed of by individuals in the urban public area. This system deploys a high-resolution camera to capture waste image and sensors to detect other useful feature information. The MHS uses a CNN-based algorithm to extract image features and a multilayer perceptrons (MLP) method to consolidate image features and other feature information to classify wastes as recyclable or the others. The MHS is trained and validated against the manually labelled items, achieving overall classification accuracy higher than 90% under two different testing scenarios, which significantly outperforms a reference CNN-based method relying on image-only inputs. [ABSTRACT FROM AUTHOR]
- Subjects :
- DEEP learning
WASTE management
WASTE recycling
ALGORITHMS
MULTILAYER perceptrons
Subjects
Details
- Language :
- English
- ISSN :
- 16875265
- Database :
- Complementary Index
- Journal :
- Computational Intelligence & Neuroscience
- Publication Type :
- Academic Journal
- Accession number :
- 132770354
- Full Text :
- https://doi.org/10.1155/2018/5060857