3 papers
cs.CV2026
Hybrid Quantum-Classical AI for Industrial Defect Classification in Welding Images
Akshaya Srinivasan, Xiaoyin Cheng, Jianming Yi +4
Hybrid quantum-classical machine learning offers a promising direction for advancing automated quality control in industrial settings. In this study, we investigate two hybrid quan…
cs.CE2026
Learning Where the Physics Is: Probabilistic Adaptive Sampling for Stiff PDEs
Akshay Govind Srinivasan, Balaji Srinivasan
Modeling stiff partial differential equations (PDEs) with sharp gradients remains a significant challenge for scientific machine learning. While Physics-Informed Neural Networks (P…
cs.CV2024
Benefiting from Quantum? A Comparative Study of Q-Seg, Quantum-Inspired Techniques, and U-Net for Crack Segmentation
Akshaya Srinivasan, Alexander Geng, Antonio Macaluso +2
Exploring the potential of quantum hardware for enhancing classical and real-world applications is an ongoing challenge. This study evaluates the performance of quantum and quantum…