Results 91 to 100 of about 14,166 (237)

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

Deep Learning Models for Detection of Periapical Radiolucent Lesions on Panoramic Radiographs: A Systematic Review and Meta‐Analysis

International Endodontic Journal, EarlyView.
ABSTRACT Background Panoramic radiographs are used routinely to screen dental conditions and treatment patterns. Recently, numerous studies have suggested that deep learning (DL) models can be utilized for analysing panoramic radiographs. Objective This review aimed to evaluate the accuracy of DL models in detecting periapical radiolucent lesions (PRLs)
Ibrahim Ali Ahmad, Raidan Ba‐Hattab, Sadeq Ali Al‐Maweri, Faleh Tamimi   +3 more
wiley   +1 more source

An Artificial Intelligence-Based System for Identifying Ureteral Stricture Regions [PDF]

International Neurourology Journal
Purpose This paper proposes a technical system designed to accurately identify the stenotic site in patients with ureteral stricture and guide the surgeon. The objective of this technical solution is to improve surgical efficiency.
Jong Mok Park, Khae-Hawn Kim
doaj   +1 more source

Deep Learning for Assessing Caries Depth in Permanent Teeth Using Intraoral Radiographs: A Systematic Review

International Endodontic Journal, EarlyView.
ABSTRACT Background Accurate assessment of caries depth on intraoral radiographs is crucial for determining the extent of the lesion and planning appropriate treatment. Artificial intelligence (AI) models have been increasingly used for detecting and classifying carious lesions; however, the evidence focusing specifically on the classification of ...
Laith Abu Qdais, Richard Gault, Jamie Toole, Aysar Khudair, Omer Butt, Ikhlas El‐Karim   +5 more
wiley   +1 more source

AI‐Assisted Literature Mining Reveals Spatiotemporal Heterogeneity and Progression Trajectories of Traditional Chinese Medicine Syndromes in Coronary Heart Disease in China

Journal of Evidence-Based Medicine, EarlyView.
ABSTRACT Despite the centrality of syndrome differentiation in guiding personalized traditional Chinese medicine (TCM) interventions for coronary heart disease (CHD), existing studies of TCM syndrome distribution are constrained by fragmented methodologies and limited spatiotemporal resolution. In this study, we employed an artificial intelligence (AI)‐
Qianzi Che, Tian Song, Zhaoyuan Gong, Chuxuan Wang, Bin Liu, Mingzhi Hu, Ning Liang, Haili Zhang, Huizhen Li, Qingyang Zeng, Lin Chen, Yuanming Leng, Xihao Cao, Jing Wan, Jing Guo, Nannan Shi   +15 more
wiley   +1 more source

Yolov5s-PSG: Improved Yolov5s-Based Helmet Recognition in Complex Scenes

IEEE Access
In the field of industrial safety, due to the existence of color, distance and other reasons in complex industrial environments caused by the helmet small target detection methods have the problem of misdetection and omission, and the Yolov5s model for real-time detection of helmets is not ideal.
Yi Li 0077, Xiaolin Shi, Xiaolong Xu, Han Zhang, Fan Yang   +4 more
openaire   +2 more sources

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

R‐YOLOv5s: Improved YOLOv5s for Object Detection in Low‐Light Environments

International Journal of Intelligent Systems
In response to the challenge of low detection accuracy exhibited by mainstream object detection models in low‐light environments, this paper proposes a novel detection model named R‐YOLOv5s. The model incorporates several key enhancements to address this issue.
Yimeng Xia, Yuanmei Wang, Hao Luo, Shengzhe Liu, Tao Li   +4 more
openaire   +2 more sources

Guiding the AI revolution in periodontology and implant dentistry: Concepts, ethics, accountability, and a roadmap for sustainable adoption

Periodontology 2000, EarlyView.
Abstract Background Artificial intelligence (AI) is increasingly gaining attention in the field of periodontology and implant dentistry. Currently developed models can support diagnosis, treatment planning, and maintenance monitoring. However, most of the available literature is based on retrospective and often single‐modality data sets.
Aminollah Khormali, Negin Soghli, Patricia A. Miguez   +2 more
wiley   +1 more source

Improved Efficiency and Lesion Detection in Small Bowel Capsule Endoscopy Using the Open‐Source Artificial Intelligence Model SEE‐AI

DEN Open, Volume 7, Issue 1, April 2027.
AI‐assisted reading with the open‐source SEE‐AI model improves lesion detection sensitivity and reduces reading time in small‐bowel capsule endoscopy. In a multicenter retrospective study of 249 cases, SEE‐AI provides visual cues that support physicians during interpretation while preserving physician‐led final decisions.
Satoshi Miyazono, Junji Umeno, Tomohiro Nagasue, Takuto Saiki, Hisamitsu Kaku, Takehiro Torisu, Akihito Yokote, Keisuke Kawasaki, Yutaro Ihara, Yuichi Matsuno, Noriyuki Imazu, Tomohiko Moriyama, Ahmed Nashaat Mohamed, Katsuya Hirakawa, Hajime Yamagata, Yasuharu Okamoto, Koichi Kurahara, Shinichiro Yada, Akira Harada, Tetsuro Ago   +19 more
wiley   +1 more source