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 …

The accumulation of solid waste in the urban area is becoming a great concern, and it would
result in environmental pollution and may be hazardous to human health if it is not properly …

Parallel to the rapid growth of the population, the rate of consumption is increasing all over
the world; this causes significant increases in the amount of waste. Thanks to the recycling of …

The rapid advancement of deep learning technology has led to the presentation of various
network architectures for classification, making it easier to implement intelligent waste …

This study aims to improve the accuracy of waste sorting through deep learning and to
provide a possibility for intelligent waste classification based on computer vision/mobile …

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 …

The proper handling of waste is one of the biggest challenges of modern society. Municipal
Solid Waste (MSW) requires categorization into a number of types, including bio, plastic …

An automatic classification robot based on effective image recognition could help reduce
huge labors of recycling tasks. Convolutional neural network (CNN) model, such as …

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 …

Waste management leads to the demolition of waste conducted by recycling and landfilling.
Deep learning and the Internet of things (IoT) confer an agile solution in classification and …