A5071454135- Impact of Light on Environment and Health
- Autonomous Vehicle Technology and Safety
- Land Use and Ecosystem Services
- Urban Green Space and Health
- Urban Heat Island Mitigation
- Advanced Database Systems and Queries
- Video Surveillance and Tracking Methods
- Automated Road and Building Extraction
- Archaeology and Natural History
- Socioeconomics of Resources and Conservation
- Data Visualization and Analytics
- Human Mobility and Location-Based Analysis
- Traffic Prediction and Management Techniques
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Data Management and Algorithms
- Botany, Ecology, and Taxonomy Studies
- Urban Transport and Accessibility
- Noise Effects and Management
- Vehicle License Plate Recognition
University College London
2022-2024
Cities are complex systems that constantly changing. This paper explores the capabilities of using crowdsourced street-level imagery in observing city dynamics. Visual walkability is an example such index, where different results may be obtained depending on locational and temporal factors. introduces a new index called Type Walkability (TVW) to characterize classify visual Inner London utilizing Mapillary images. The method based panoptic segmentation, pixel-level segmentation instance...
The precise recognition of urban fringes is vital to monitor sprawl and map management planning. spatial clustering method a prevalent way identify due its objectivity convenience. However, previous studies had problems with ignoring heterogeneity, which could overestimate or underestimate the results. Nighttime light can reflect transitional urban–rural regions’ regional characteristics be used fringes. Accordingly, new model has been established for fringe identification by combining...
Road traffic crashes cause millions of deaths annually and have a significant economic impact, particularly in low- middle-income countries (LMICs). This paper presents an approach using Vision Language Models (VLMs) for road safety assessment, overcoming the limitations traditional Convolutional Neural Networks (CNNs). We introduce new task ,V-RoAst (Visual question answering Assessment), with real-world dataset. Our optimizes prompt engineering evaluates advanced VLMs, including...
Panoramic cycling videos can record 360{\deg} views around the cyclists. Thus, it is essential to conduct automatic road user analysis on them using computer vision models provide data for studies safety. However, features of panoramic such as severe distortions, large number small objects and boundary continuity have brought great challenges existing CV models, including poor performance evaluation methods that are no longer applicable. In addition, due lack with annotations, not easy...
Walkability is becoming increasingly important in urban planning, public health, and environmental protection. Traditional assessment tools like streetscape images semantic segmentation focus on objective factors, while questionnaires as the main tool for perceived walkability are limited by cost scale. This study introduces a new method using Multimodal Contrastive Learning Model, CLIP, to assess analysing both tangible subjective factors such safety attractiveness. The compares with...