26 citations · 34 across the 6 of their papers we have counts for
7 papers
Human Mobility Reimagined: Digital Twin Intelligence for Adaptive Campus Course Timetabling
Keshu Wu, Xinyue Ye, Suphanut Jamonnak +1
Daily operations in large campuses depend on how efficiently people \emph{move} through space and time. In this sense, course timetables are more than administrative schedules: the…
Integrating Spatiotemporal Vision Transformer into Digital Twins for High-Resolution Heat Stress Forecasting in Campus Environments
Wenjing Gong, Xinyue Ye, Keshu Wu +4
Extreme heat events, exacerbated by climate change, pose significant challenges to urban resilience and planning. This study introduces a climate-responsive digital twin framework…
CLIP-S: Language-Guided Self-Supervised Semantic Segmentation
Wenbin He, Suphanut Jamonnak, Liang Gou +1
Existing semantic segmentation approaches are often limited by costly pixel-wise annotations and predefined classes. In this work, we present CLIP-S that leverages self-supervi…
Geo-Context Aware Study of Vision-Based Autonomous Driving Models and Spatial Video Data
Suphanut Jamonnak, Ye Zhao, Xinyi Huang +1
Vision-based deep learning (DL) methods have made great progress in learning autonomous driving models from large-scale crowd-sourced video datasets. They are trained to predict in…
Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images
Xinyi Huang, Suphanut Jamonnak, Ye Zhao +4
Existing interactive visualization tools for deep learning are mostly applied to the training, debugging, and refinement of neural network models working on natural images. However…
Multi-dimensional Skyline Query to Find Best Shopping Mall for Customers
Md Amiruzzaman, Suphanut Jamonnak
This paper presents a new application for multi-dimensional Skyline query. The idea presented in this paper can be used to find best shopping malls based on users requirements. A w…
Visual Understanding of Multiple Attributes Learning Model of X-Ray Scattering Images
Xinyi Huang, Suphanut Jamonnak, Ye Zhao +4
This extended abstract presents a visualization system, which is designed for domain scientists to visually understand their deep learning model of extracting multiple attributes i…