Plastic Waste Classification Using CNN for Supporting 3R's Principle
Plastic isn't as simple as everyone assume. The world now produces more than 380 million
tons of plastic, half of this is utilized to make one-use items such as polythene bags, mugs …
tons of plastic, half of this is utilized to make one-use items such as polythene bags, mugs …
Waste profiling and analysis using machine learning
F Shaikh, N Kazi, F Khan… - 2020 second international …, 2020 - ieeexplore.ieee.org
A large amount of solid waste is generated in the urban areas, and these wastes contain
different types of substances like organic wastes, paper, plastic, metal, glass, etc. which …
different types of substances like organic wastes, paper, plastic, metal, glass, etc. which …
A smart waste classification model using hybrid CNN-LSTM with transfer learning for sustainable environment
Waste collection, classification, and planning have become crucial as industrialization and
smart city advancement activities have increased. A recycling process of waste relies on the …
smart city advancement activities have increased. A recycling process of waste relies on the …
An approach to waste segregation and management using convolutional neural networks
Population explosion in India has led to an outburst of some major concerns, one of which is
the waste generation and disposal system. India is accountable for producing 12% of the …
the waste generation and disposal system. India is accountable for producing 12% of the …
Waste classification using AutoEncoder network with integrated feature selection method in convolutional neural network models
Unless adequate measures are taken for waste litter, the ecological balance may deteriorate
over time. The wastes disposed of the trash can be divided into two classes that are organic …
over time. The wastes disposed of the trash can be divided into two classes that are organic …
The use of modern technology in smart waste management and recycling: artificial intelligence and machine learning
Waste management is one of the primary problem that the world faces irrespective of the
case of developed or developing country. The key issue in the waste management is that the …
case of developed or developing country. The key issue in the waste management is that the …
Automated biomass recycling management system using modified grey wolf optimization with deep learning model
Biomass residues encompass non-recyclable municipal solid waste, crop wastes, sewage
effluents and sludges, domestic and industrial greywater, etc. Numerous wastes to energy …
effluents and sludges, domestic and industrial greywater, etc. Numerous wastes to energy …
[PDF][PDF] Detection of waste materials using deep learning and image processing
A Mitra - 2020 - scholarworks.calstate.edu
The process of segregating waste prompts the generation of energy out of waste,
diminishing landfills, recycling, and reduction of waste. Erroneous disposal of waste leads to …
diminishing landfills, recycling, and reduction of waste. Erroneous disposal of waste leads to …
[PDF][PDF] Image based trash classification using machine learning algorithms for recyclability status
M Satvilkar - 2018 - norma.ncirl.ie
This research paper talks about Trash classification which comes across as a social and
unique cause where Image processing through Analytics can help with better management …
unique cause where Image processing through Analytics can help with better management …
AI based waste classifier with thermo-rapid composting
SK Behera, L Vasundhara, G Saisudha… - … on Power, Energy …, 2020 - ieeexplore.ieee.org
Waste management is a certainly a very complex and difficult process especially in very
large cities. It needs immense man power and also uses up other resources such as …
large cities. It needs immense man power and also uses up other resources such as …