3 papers
cs.LG2026
Walkable to Whom? Capturing Subjective Variability in Walkability Perception Using Multimodal Deep Learning
Moloud Damandeh, Meead Saberi
Visual perception of walkability varies substantially across individuals, reflecting differences in personal characteristics, experiences, and preferences. Existing studies, howeve…
cs.LG2025
INSPIRE-GNN: Intelligent Sensor Placement to Improve Sparse Bicycling Network Prediction via Reinforcement Learning Boosted Graph Neural Networks
Mohit Gupta, Debjit Bhowmick, Rhys Newbury +3
Accurate link-level bicycling volume estimation is essential for sustainable urban transportation planning. However, many cities face significant challenges of high data sparsity d…
cs.LG2025
Evaluating the effects of Data Sparsity on the Link-level Bicycling Volume Estimation: A Graph Convolutional Neural Network Approach
Mohit Gupta, Debjit Bhowmick, Meead Saberi +2
Accurate bicycling volume estimation is crucial for making informed decisions and planning about future investments in bicycling infrastructure. However, traditional link-level vol…