6 papers
LadderTeam: Dual-Agent Laddering Elicitation Framework
Manjushree Aithal, Alexander Kotz, James Mitchell
Eliciting detailed and actionable software requirements from end-users is a critical phase in the iterative development of a software product or application. To ensure the feedback…
PLACID: Privacy-preserving Large language models for Acronym Clinical Inference and Disambiguation
Manjushree B. Aithal, Ph. D., Alexander Kotz +2
Large Language Models (LLMs) offer transformative solutions across many domains, but healthcare integration is hindered by strict data privacy constraints. Clinical narratives are…
LENVIZ: A High-Resolution Low-Exposure Night Vision Benchmark Dataset
Manjushree Aithal, Rosaura G. VidalMata, Manikandtan Kartha +6
Low-light image enhancement is crucial for a myriad of applications, from night vision and surveillance, to autonomous driving. However, due to the inherent limitations that come i…
Unified-EGformer: Exposure Guided Lightweight Transformer for Mixed-Exposure Image Enhancement
Eashan Adhikarla, Kai Zhang, Rosaura G. VidalMata +5
Despite recent strides made by AI in image processing, the issue of mixed exposure, pivotal in many real-world scenarios like surveillance and photography, remains inadequately add…
Boundary Defense Against Black-box Adversarial Attacks
Manjushree B. Aithal, Xiaohua Li
Black-box adversarial attacks generate adversarial samples via iterative optimizations using repeated queries. Defending deep neural networks against such attacks has been challeng…
Mitigating Black-Box Adversarial Attacks via Output Noise Perturbation
Manjushree B. Aithal, Xiaohua Li
In black-box adversarial attacks, adversaries query the deep neural network (DNN), use the output to reconstruct gradients, and then optimize the adversarial inputs iteratively. In…