4 citations · 7 across the 6 of their papers we have counts for
8 papers · 1 filter
HSI-Road Relabeled: Surface-Aware Road-Scene Segmentation
Imad Ali Shah, Imran Mehmood, Enda Ward +3
The HSI-Road dataset provides paired RGB and 25-channel NIR (600--960~nm) images with binary masks but no surface-level labels.~This paper introduces a manually labeled six-class t…
Learnable Quantum Efficiency Filters for Urban Hyperspectral Segmentation
Imad Ali Shah, Jiarong Li, Ethan Delaney +4
Hyperspectral sensing provides rich spectral information for scene understanding in urban driving, but its high dimensionality poses challenges for interpretation and efficient lea…
Hyperspectral Sensors and Autonomous Driving: Technologies, Limitations, and Opportunities
Imad Ali Shah, Jiarong Li, Roshan George +5
Hyperspectral imaging (HSI) offers a transformative sensing modality for Advanced Driver Assistance Systems (ADAS) and autonomous driving (AD) applications, enabling material-level…
Hyperspectral vs. RGB for Pedestrian Segmentation in Urban Driving Scenes: A Comparative Study
Jiarong Li, Imad Ali Shah, Enda Ward +3
Pedestrian segmentation in automotive perception systems faces critical safety challenges due to metamerism in RGB imaging, where pedestrians and backgrounds appear visually indist…
CSNR and JMIM Based Spectral Band Selection for Reducing Metamerism in Urban Driving
Jiarong Li, Imad Ali Shah, Diarmaid Geever +5
Protecting Vulnerable Road Users (VRU) is a critical safety challenge for automotive perception systems, particularly under visual ambiguity caused by metamerism, a phenomenon wher…
Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios
Imad Ali Shah, Jiarong Li, Tim Brophy +4
Recent advances in autonomous driving (AD) have highlighted the potential of hyperspectral imaging (HSI) for enhanced environmental perception, particularly in challenging weather…