With the rise of deep learning technologies, the landscape of recycling plant automation has
dramatically transformed. This paper presents a pioneering application of YOLOv4 in …

Deep neural networks (DNNs) play an important role in our daily lives, from aiding us in
menial tasks to solving world issues such as cancer cell detection. However, few pieces of …

Waste sorting is highly labor intensive because the wide variety of waste items prohibits
automation. More recently, deep learning (DL) and computer vision technology has …

The importance of recycling to the environment and economy is well known. The existing
manual labor and traditional industrial sorting technology have low efficiency, poor …

Plastic waste is a growing environmental concern that poses a significant threat to onshore
ecosystems, human health, and wildlife. The accumulation of plastic waste in oceans has …

Garbage classification and recycling have a lot of benefits, which help protect water and soil
resources, improve the living environment's quality, and speed up the green circular …

The increased global waste generation rates over the last few decades have made the
waste management task a significant problem. One of the potential approaches adopted …

With the increasing focus on environmental conservation, efficient and accurate waste
classification has become a crucial task in the face of increasing urbanisation and …

This paper deals with the detection and classification of waste materials by performing an
analysis of the deep learning-based computer vision techniques. Object detection and …

Plastic pollution has emerged as a major global concern due to its enduring nature and
limited recycling options. In response to this critical challenge, this paper presents a novel …