Plastic waste detection on rivers using YOLOv5 algorithm

GA Sio, D Guantero, J Villaverde - 2022 13th International …, 2022 - ieeexplore.ieee.org
Building sustainable, clean communities have always been a challenge, especially with the
surge in population that increases waste and rubbish production. A higher pollution level …

Low resource deep learning to detect waste intensity in the river flow

FF Putra, YD Prabowo - Bulletin of Electrical Engineering and Informatics, 2021 - beei.org
Waste has become a significant problem in Indonesia, especially in the capital city of Jakarta
due to many disasters caused by it. The one cause of flooding is the blockage of river flow by …

A comparison of RGB and RGNIR color spaces for plastic waste detection using the YOLOv5 architecture

O Tamin, EG Moung, JA Dargham… - … in Engineering and …, 2022 - ieeexplore.ieee.org
Plastic waste is a serious environmental issue that damages human health, wildlife, and
habitats. Many researchers have come out with multiple solutions on the problem. One of the …

A novel finetuned YOLOv8 model for real-time underwater trash detection

C Gupta, NS Gill, P Gulia, S Yadav… - Journal of Real-Time …, 2024 - Springer
When recognizing underwater images, problems, including poor image quality and
complicated backdrops, are significant. The main problem of underwater images is the …

The Object Detection of Underwater Garbage with an Improved YOLOv5 Algorithm

X Teng, Y Fei, K He, L Lu - … of the 2022 International Conference on …, 2022 - dl.acm.org
Litter deposition in aquatic environments has devastating effects on marine ecological
environment and poses a threat to a sustainable economy. Autonomous Underwater …

[HTML][HTML] Solid Waste Detection Using Enhanced YOLOv8 Lightweight Convolutional Neural Networks

P Li, J Xu, S Liu - Mathematics, 2024 - mdpi.com
As urbanization accelerates, solid waste management has become one of the key issues in
urban governance. Accurate and efficient waste sorting is a crucial step in enhancing waste …

Object detection for hazardous material vehicles based on improved YOLOv5 algorithm

P Zhu, B Chen, B Liu, Z Qi, S Wang, L Wang - Electronics, 2023 - mdpi.com
Hazardous material vehicles are a non-negligible mobile source of danger in transport and
pose a significant safety risk. At present, the current detection technology is well developed …

Waste collection and transportation supervision based on improved YOLOv3 model

Y He, J Li, S Chen, Y Xu, J Liang - IEEE Access, 2022 - ieeexplore.ieee.org
Supervising the process of garbage collection and transportation is a very crucial task with
significance implication to the reusing and the recycle of the garbage. Previous works mainly …

Visual detection of waste using YOLOv8

R Bawankule, V Gaikwad, I Kulkarni… - … and Smart Systems …, 2023 - ieeexplore.ieee.org
With the increasing focus on environmental conservation, efficient and accurate waste
classification has become a crucial task in the face of increasing urbanisation and …

YOLO-based Network Fusion for Riverine Floating Debris Monitoring System

NA Zailan, ASM Khairuddin… - 2021 International …, 2021 - ieeexplore.ieee.org
Riverine floating debris has been one of the major challenges and a well-known issue
across the globe for decades. To mitigate this problem, sources of debris and their pathways …