Results 71 to 80 of about 6,685 (188)

Augmentation for Accuracy Improvement of YOLOv8 in Blind Navigation System

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
This study addresses the critical need for enhanced accuracy in YOLOv8 models designed for visually impaired navigation systems. Existing models often struggle with consistency in object detection and distance estimation under varying environmental ...
Erwin Syahrudin, Ema Utami, Anggit Dwi Hartanto   +2 more
doaj   +1 more source

Plant Disease Detection and Classification Using Deep Learning Methods: A Comparison Study

Journal of Informatics and Web Engineering
The presence issue of inaccurate plant disease detection persists under real field conditions and most deep learning (DL) techniques still struggle to achieve real-time performance.
Pei-Wern Chin, Kok-Why Ng, Naveen Palanichamy   +2 more
doaj   +1 more source

SW‐YOLO: An Optimized YOLOv8 Architecture With ConvNeXt for Real‐Time and Accurate Substation Wiring Inspection

Engineering Reports, Volume 8, Issue 3, March 2026.
The study uses affine transformation, contrast enhancement, and mosaic masking for image enhancement and introduces the Convolutional NeXt module in YOLOv8 based on masked self‐encoder and response normalization, along with improvements to the convolutional block attention module.
Yu Lei, Zhihao Liang, Jiayun Huang
wiley   +1 more source

Real‐Time Vision System for Estimating Magnetic Compass Needle Oscillation Using Deep Learning

Engineering Reports, Volume 8, Issue 3, March 2026.
This study presents a low‐cost, vision‐based system for measuring compass needle oscillation. The system uses YOLO11s to detect the needle's pivot and tip in real time. Angle‐time data is tracked and fitted to extract oscillation parameters. The method is fast, accurate, and suitable for embedded navigation systems. ABSTRACT Compass needle oscillations
Xuan‐Thuan Nguyen, Hong‐Hai Hoang, Thanh‐Hung Nguyen   +2 more
wiley   +1 more source

Optimizing traffic management in Danang: a comparative study of multi-object tracking techniques for real-time vehicle flow monitoring

Tạp chí Khoa học và Công nghệ
This study evaluates the effectiveness of various detection-based object-tracking algorithms to optimize accuracy and efficiency in traffic flow monitoring. Due to its high accuracy in detecting objects, YOLOv8 was chosen as the vehicle detector for this
Hai T. Ton, Hung V. Nguyen, Hanh T. M. Tran, Tien V. Thai, Phong-Phu Le, Tung T. Huynh, Duy-Tuan Dao   +6 more
doaj   +1 more source

Using Convolutional Neural Networks for the Classification of Suboptimal Chest Radiographs

Journal of Medical Radiation Sciences, Volume 73, Issue 1, Page 60-68, March 2026.
This study evaluated DenseNet121 and YOLOv8 neural networks in detecting suboptimal chest x‐rays for quality control. Through training, validation, and testing, both AI models effectively classified chest X‐ray quality, highlighting the potential to provide radiographers with feedback to enhance image quality.
Emily Huanke Liu, Daniel Carrion, Mohamed Khaldoun Badawy   +2 more
wiley   +1 more source

CSD-YOLOv8s: Dense Sheep Small Target Detection Model Based on UAV Images

智慧农业
ObjectiveThe monitoring of livestock grazing in natural pastures is a key aspect of the transformation and upgrading of large-scale breeding farms. In order to meet the demand for large-scale farms to achieve accurate real-time detection of a large ...
WENG Zhi, LIU Haixin, ZHENG Zhiqiang
doaj   +1 more source

QL-YOLOv8s: Precisely Optimized Lightweight YOLOv8 Pavement Disease Detection Model

IEEE Access
Detecting road surface defects is essential for highway maintenance, yet the application of most models is hindered by the limitations of existing detection resources. To address this challenge, we have enhanced YOLOv8, introducing a lightweight detection model dubbed QL-YOLOv8s.
Guo Jinbo, Wang Shenghuai, Chen Xiaohui, Wang Chen, Zhang Wei   +4 more
openaire   +2 more sources

Artificial Intelligence for Radiographic Image Quality: Radiographers at the Forefront

Journal of Medical Radiation Sciences, Volume 73, Issue 1, Page 3-6, March 2026.
This editorial highlights the central role of radiographers in leading AI‐driven radiographic image‐quality assessment. It outlines how AI can enhance real‐time feedback, support consistency, and strengthen safe, patient‐centered imaging practice.
Kamarul Amin Abdullah
wiley   +1 more source

A Regional Farming Pig Counting System Based on Improved Instance Segmentation Algorithm

智慧农业
ObjectiveCurrently, pig farming facilities mainly rely on manual counting for tracking slaughtered and stored pigs. This is not only time-consuming and labor-intensive, but also prone to counting errors due to pig movement and potential cheating.
ZHANG Yanqi, ZHOU Shuo, ZHANG Ning, CHAI Xiujuan, SUN Tan   +4 more
doaj   +1 more source