[HTML][HTML] Automated Dual-Side Leather Defect Detection and Classification Using YOLOv11: A Case Study in the Finished Leather Industry
This study explores the optimization of leather defect detection through the advanced
YOLOv11 model, addressing long-standing challenges in quality control within the leather …
YOLOv11 model, addressing long-standing challenges in quality control within the leather …
[HTML][HTML] Evaluation of Pothole Detection Performance Using Deep Learning Models Under Low-Light Conditions
Y Zanevych, V Yovbak, O Basystiuk, N Shakhovska… - Sustainability, 2024 - mdpi.com
In our interconnected society, prioritizing the resilience and sustainability of road
infrastructure has never been more critical, especially in light of growing environmental and …
infrastructure has never been more critical, especially in light of growing environmental and …
Efficient Detection Framework Adaptation for Edge Computing: A Plug-and-play Neural Network Toolbox Enabling Edge Deployment
J Wu, S Zhang, S Chen, L Wang, Z Wang… - arxiv preprint arxiv …, 2024 - arxiv.org
Edge computing has emerged as a key paradigm for deploying deep learning-based object
detection in time-sensitive scenarios. However, existing edge detection methods face …
detection in time-sensitive scenarios. However, existing edge detection methods face …
Performance Benchmarking of YOLOv11 Variants for Real-Time Delivery Vehicle Detection: A Study on Accuracy, Speed, and Computational Trade-offs
R Kishor - Asian Journal of Research in Computer Science, 2024 - hal.science
The YOLOv series represents state-of-the-art technology for single-stage object detection,
excelling in speed and accuracy. In many scenarios, it outperforms traditional two-stage …
excelling in speed and accuracy. In many scenarios, it outperforms traditional two-stage …
Advancing Arecanut Quality Grading: A Comparative Analysis of YOLO Models with Hyperparameter Optimization
Arecanut grading is essential for maintaining quality, fair pricing, and efficient trade. Manual
grading methods, dependent on subjective human assessment, are prone to errors …
grading methods, dependent on subjective human assessment, are prone to errors …
APF-YOLOV8: Enhancing Multiscale Detection and Intra-Class Variance Handling for UAV-Based Insulator Power Line Inspections
R Aitelhaj, BE Benelmostafa, H Medromi - F1000Research, 2025 - f1000research.com
Background UAV-based power line inspections offer a safer, more efficient alternative to
traditional methods, but insulator detection presents key challenges: multiscale object …
traditional methods, but insulator detection presents key challenges: multiscale object …
Defect Detection Network In PCB Circuit Devices Based on GAN Enhanced YOLOv11
This study proposes an advanced method for surface defect detection in printed circuit
boards (PCBs) using an improved YOLOv11 model enhanced with a generative adversarial …
boards (PCBs) using an improved YOLOv11 model enhanced with a generative adversarial …
From Crown Detection to Boundary Segmentation: Advancing Forest Analytics with Enhanced YOLO Model and Airborne LiDAR Point Clouds
Y Liu, A Zhang, P Gao - Forests, 2025 - mdpi.com
Individual tree segmentation is crucial to extract forest structural parameters, which is vital for
forest resource management and ecological monitoring. Airborne LiDAR (ALS), with its …
forest resource management and ecological monitoring. Airborne LiDAR (ALS), with its …