Application of MobileNetV2 to waste classification. [PDF]
PLoS One, 2023 Today, the topic of waste separation has been raised for a long time, and some waste separation devices have been installed in large communities. However, the vast majority of domestic waste is still not properly sorted and put out, and the disposal of domestic waste still relies mostly on manual classification.
Yong L, Ma L, Sun D, Du L.
europepmc +5 more sources
A Systematic Review of AI-Based Techniques for Automated Waste Classification [PDF]
SensorsWaste classification is a critical step in waste management that is time-consuming and necessitates automation to replace traditional approaches. Recently, machine learning (ML) and deep learning (DL) have gained attention from researchers seeking to ...
Farnaz Fotovvatikhah +3 more
doaj +3 more sources
A deep learning approach for medical waste classification. [PDF]
Sci Rep, 2022 As the demand for health grows, the increase in medical waste generation is gradually outstripping the load. In this paper, we propose a deep learning approach for identification and classification of medical waste.
Zhou H +15 more
europepmc +2 more sources
Intelligent and sustainable waste classification model based on multi-objective beluga whale optimization and deep learning. [PDF]
Environ Sci Pollut Res IntResource recycling is considered necessary for sustainable development, especially in smart cities where increased urbanization and the variety of waste generated require the development of automated waste management models.
Sayed GI +3 more
europepmc +2 more sources
Focus-RCNet: a lightweight recyclable waste classification algorithm based on focus and knowledge distillation. [PDF]
Vis Comput Ind Biomed Art, 2023 Waste pollution is a significant environmental problem worldwide. With the continuous improvement in the living standards of the population and increasing richness of the consumption structure, the amount of domestic waste generated has increased ...
Zheng D, Wang R, Duan Y, Pang PC, Tan T.
europepmc +2 more sources
Real Time Multipurpose Smart Waste Classification Model for Efficient Recycling in Smart Cities Using Multilayer Convolutional Neural Network and Perceptron [PDF]
Sensors, 2021 Urbanization is a big concern for both developed and developing countries in recent years. People shift themselves and their families to urban areas for the sake of better education and a modern lifestyle.
Ali Usman Gondal +9 more
doaj +2 more sources
Blockchain based solid waste classification with AI powered tracking and IoT integration. [PDF]
Sci RepSmart waste management is vital for reducing environmental impact and improving quality of life in smart cities. This study presents an AI-driven waste classification model that integrates IoT and Blockchain technologies. IoT-connected bins transmit data
Alabdali AM.
europepmc +2 more sources
Towards sustainable solutions: Effective waste classification framework via enhanced deep convolutional neural networks. [PDF]
PLoS OneAs industrialization and the development of smart cities progress, effective waste collection, classification, and management have become increasingly vital.
Islam MM +4 more
europepmc +2 more sources
Optimizing Backbone Networks Through Hybrid–Modal Fusion: A New Strategy for Waste Classification [PDF]
SensorsWith rapid urbanization, effective waste classification is a critical challenge. Traditional manual methods are time-consuming, labor-intensive, costly, and error-prone, resulting in reduced accuracy.
Houkui Zhou +9 more
doaj +2 more sources
Can the implementation of household waste classification mitigate greenhouse gas emissions in Beijing? A comprehensive analysis of recent trends and future scenarios [PDF]
Heliyon, 2023 Household waste contributes significantly to global greenhouse gas (GHG) emissions, and waste classification is crucial for reducing emissions. This study focuses on Beijing and utilizes life cycle assessment (LCA) and material flow analysis (MFA) to ...
Zhixin Wen +4 more
doaj +2 more sources