3 papers
cs.CV2026
HiLRP: Toward One Trustworthy Explanation for Vision Transformer: Conservation-Valid Attribution via Attention Primitives
Sathiyamohan Nishankar, Pubudu Sanjeewani, Asanka Perera +1
Vision Transformer (ViT) design has become increasingly diverse, with backbones combining convolutional stems, windowed, linear, or multi-axis attention, patch merging, and spatial…
cs.CV2026
Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs
Sathiyamohan Nishankar, Nethmi Pathirana, Pubudu Sanjeewani +2
Most evidence on the effectiveness of explainable artificial intelligence (XAI) attribution methods has been established on convolutional neural networks (CNNs), with limited inves…
cs.CV2025
Benchmarking CNN and Transformer-Based Object Detectors for UAV Solar Panel Inspection
Ashen Rodrigo, Isuru Munasinghe, Pubudu Sanjeewani +1
Timely and accurate detection of defects and contaminants in solar panels is critical for maintaining the efficiency and reliability of photovoltaic (PV) systems. While recent stud…