Application of machine learning methods for the prediction of organic solid waste treatment and recycling processes: A review
H Guo, S Wu, Y Tian, J Zhang, H Liu - Bioresource technology, 2021 - Elsevier
Conventional treatment and recycling methods of organic solid waste contain inherent flaws,
such as low efficiency, low accuracy, high cost, and potential environmental risks. In the past …
such as low efficiency, low accuracy, high cost, and potential environmental risks. In the past …
Computer vision for solid waste sorting: A critical review of academic research
Waste sorting is highly recommended for municipal solid waste (MSW) management.
Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW …
Increasingly, computer vision (CV), robotics, and other smart technologies are used for MSW …
[HTML][HTML] A review on chemometric techniques with infrared, Raman and laser-induced breakdown spectroscopy for sorting plastic waste in the recycling industry
Mismanagement of plastic waste globally has resulted in a multitude of environmental
issues, which could be tackled by boosting plastic recycling rates. Chemometrics has …
issues, which could be tackled by boosting plastic recycling rates. Chemometrics has …
Recycling waste classification using optimized convolutional neural network
An automatic classification robot based on effective image recognition could help reduce
huge labors of recycling tasks. Convolutional neural network (CNN) model, such as …
huge labors of recycling tasks. Convolutional neural network (CNN) model, such as …
Forecasting plastic waste generation and interventions for environmental hazard mitigation
Plastic waste and its environmental hazards have been attracting public attention as a
global sustainability issue. This study builds a neural network model to forecast plastic waste …
global sustainability issue. This study builds a neural network model to forecast plastic waste …
[HTML][HTML] Optical sensors and machine learning algorithms in sensor-based material flow characterization for mechanical recycling processes: A systematic literature …
Digital technologies hold enormous potential for improving the performance of future-
generation sorting and processing plants; however, this potential remains largely untapped …
generation sorting and processing plants; however, this potential remains largely untapped …
[HTML][HTML] Application of deep learning object classifier to improve e-waste collection planning
P Nowakowski, T Pamuła - Waste Management, 2020 - Elsevier
This study investigates an image recognition system for the identification and classification
of waste electrical and electronic equipment from photos. Its main purpose is to facilitate …
of waste electrical and electronic equipment from photos. Its main purpose is to facilitate …
The classification of construction waste material using a deep convolutional neural network
The management of Construction and Demolition Waste (C&DW) is complex and adds
significantly to the overall life cycle cost of projects. On site waste sorting using technologies …
significantly to the overall life cycle cost of projects. On site waste sorting using technologies …
Using computer vision to recognize composition of construction waste mixtures: A semantic segmentation approach
Timely and accurate recognition of construction waste (CW) composition can provide
yardstick information for its subsequent management (eg, segregation, determining proper …
yardstick information for its subsequent management (eg, segregation, determining proper …
A critical review of existing and emerging technologies and systems to optimize solid waste management for feedstocks and energy conversion
Solid waste generation and its accumulation is increasing at an alarming pace due to
population growth and urbanization posing severe risks to health, safety, and natural …
population growth and urbanization posing severe risks to health, safety, and natural …