Results 81 to 90 of about 17,190 (230)

YOLOv5 garbage classification method with GhostNet

Dianzi Jishu Yingyong
Garbage classification is an important part of building ecological civilization. To solve the problem that heavyweight models are difficult to deploy to mobile devices, an improved garbage image classification method based on YOLOv5 network is proposed ...
Li Yao, Hu Junguo, Le Yang
doaj   +1 more source

Smart sprayer for weed control using an object detection algorithm (YOLOv5) [PDF]

Journal of Plant Protection Research
Spraying pesticides is one of the most common procedures that is conducted to control pests. However, excessive use of these chemicals inversely affects the surrounding environments including the soil, plants, animals, and the operator itself. Therefore,
Ameer H. Al-Ahmadi, Alaa K. Subr
doaj   +1 more source

Textile and colour defect detection using deep learning methods

Coloration Technology, EarlyView.
Abstract Recent advances in deep learning (DL) have significantly enhanced the detection of textile and colour defects. This review focuses specifically on the application of DL‐based methods for defect detection in textile and coloration processes, with an emphasis on object detection and related computer vision (CV) tasks.
Hao Cui, Abdel‐Fattah Seyam, Renzo Shamey   +2 more
wiley   +1 more source

Pavement crack detection method based on improved YOLOv5

Dianzi Jishu Yingyong
Aiming at the problem that the existing crack detection model is large in size and the detection accuracy is not high, this paper proposes a crack detection method for UAV aerial images based on lightweight network.
Wang Xiangqian, Cheng Gaoli, Hu Peng, Xia Xiaohua   +3 more
doaj   +1 more source

Real Time Vessel Detection Model Using Deep Learning Algorithms for Controlling a Barrier System [PDF]

[Abstract]: This study addresses marine pollution caused by debris entering the ocean through rivers. A physical and bubble barrier system has been developed to collect debris, but an effective identification and classification system for incoming ...
Ciriano-Palacios, José M., Díaz Casás, Vicente, Ferreno-González, Sara, Folarin, Abisade, Munín-Doce, Alicia   +4 more
core   +1 more source

Artificial Intelligence in Periodontology: A Systematic Review

Journal of Periodontal Research, EarlyView.
AI shows promise across periodontology, with deep learning achieving strong performance for image‐based diagnosis of periodontitis. However, limited data diversity, inconsistent metrics, and scarce external validation raise concerns about generalizability and clinical applicability.
Antonin Tichy, Nils Werner, Helena Dujic, Charlotte Wetzel, Vinay Pitchika, Caspar Victor Bumm, Matthias Folwaczny, Falk Schwendicke   +7 more
wiley   +1 more source

PO-YOLOv5: A defect detection model for solenoid connector based on YOLOv5

PLOS ONE
Solenoid connectors play important role in electronic stability system design, with the features of small size, low cost, fast response time and high reliability. The main production process challenge for solenoid connectors is the accurate detection of defects, which is closely related to safe driving.
Ming Chen, Yuqing Liu, Xing Wei, Zichen Zhang, Oleg Gaidai, Hengshou Sui, Bin Li   +6 more
openaire   +4 more sources

DepthPark: Smart, Cost‐Effective Vision‐Based Indoor Parking Management System Using Single Monocular Depth Estimation

Applied AI Letters, Volume 7, Issue 2, June 2026.
DepthPark is a cost‐effective indoor parking management system that uses monocular cameras, two fixed cameras, and one mobile camera per parking lane, together with deep learning. By combining license plate recognition, parking‐slot classification, and single‐frame depth estimation, the system enables real‐time occupancy monitoring and parking ...
Lakshay Naresh Ramchandani, Abdsamad Benkrid   +1 more
wiley   +1 more source

Context Aware Multimodal Fusion YOLOv5 Framework for Pedestrian Detection under IoT Environment [PDF]

Radioengineering
Pedestrian detection based on deep networks has become a research hotspot in the field of computer vision. With the rapid development of the Internet of Things (IoT) and autonomous driving technology, the deployment of pedestrian detection models on ...
Y. Shu, Y. Wang, M. Zhang, J. Yang, Y. Wang, J. Wang, Y. Zhang   +6 more
doaj  

Large coal detection for belt conveyors based on improved YOLOv5

Gong-kuang zidonghua
Oversized coal blocks can easily cause poor coal flow, blockage, and coal stacking when transported on a belt conveyor. However, the differences in appearance and color between large coal blocks and ordinary coal blocks are small, and there are ...
QIN Yulong, CHENG Jiming, REN Yige, WANG Xiaoqing, ZHAO Qing, AN Cuijuan   +5 more
doaj   +1 more source