6 papers
Worst-Case Distance-Aware Error Bounds for Neural Networks
Masoud Ataei, Vikas Dhiman, Mohammad Javad Khojasteh
Safety-critical applications of machine learning require uncertainty estimates that support reliable worst-case analysis. Neural networks (NNs) provide expressive function approxim…
Weather-Aware Object Detection Transformer for Domain Adaptation
Soheil Gharatappeh, Salimeh Sekeh, Vikas Dhiman
RT-DETRs have shown strong performance across various computer vision tasks but are known to degrade under challenging weather conditions such as fog. In this work, we investigate…
Distance-Aware Error for Spline Networks: A Bottom-Up Approach to Uncertainty
Masoud Ataei, Mohammad Javad Khojasteh, Vikas Dhiman
We develop a new class of distance-aware error bounds that tightly characterize the approximation error of spline neural networks. Our bottom-up approach analyzes the error bound o…
Omobot: a low-cost mobile robot for autonomous search and fall detection
Shihab Uddin Ahamad, Masoud Ataei, Vijay Devabhaktuni +1
Detecting falls among the elderly and alerting their community responders can save countless lives. We design and develop a low-cost mobile robot that periodically searches the hou…
DADEE: Well-calibrated uncertainty quantification in neural networks for barriers-based robot safety
Masoud Ataei, Vikas Dhiman
Uncertainty-aware controllers that guarantee safety are critical for safety critical applications. Among such controllers, Control Barrier Functions (CBFs) based approaches are pop…
Cross-view geo-localization: a survey
Abhilash Durgam, Sidike Paheding, Vikas Dhiman +1
Cross-view geo-localization has garnered notable attention in the realm of computer vision, spurred by the widespread availability of copious geotagged datasets and the advancement…