9 papers
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…
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…
Vision-Language Models vs Human: Perceptual Image Quality Assessment
Imran Mehmood, Imad Ali Shah, Ming Ronnier Luo +1
Psychophysical experiments remain the most reliable approach for perceptual image quality assessment (IQA), yet their cost and limited scalability encourage automated approaches. W…
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…