2 citations · 3 across the 5 of their papers we have counts for
6 papers
MorphXAI: An Explainable Framework for Morphological Analysis of Parasites in Blood Smear Images
Aqsa Yousaf, Sint Sint Win, Megan Coffee +1
Parasitic infections remain a pressing global health challenge, particularly in low-resource settings where diagnosis still depends on labor-intensive manual inspection of blood sm…
CTMap: LLM-Enabled Connectivity-Aware Path Planning in Millimeter-Wave Digital Twin Networks
Md Salik Parwez, Sai Teja Srivillibhutturu, Sai Venkat Reddy Kopparthi +4
In this paper, we present \textit{CTMAP}, a large language model (LLM) empowered digital twin framework for connectivity-aware route navigation in millimeter-wave (mmWave) wireless…
Enhancing Graph Neural Networks: A Mutual Learning Approach
Paul Agbaje, Arkajyoti Mitra, Afia Anjum +3
Knowledge distillation (KD) techniques have emerged as a powerful tool for transferring expertise from complex teacher models to lightweight student models, particularly beneficial…
FedVLM: Scalable Personalized Vision-Language Models through Federated Learning
Arkajyoti Mitra, Afia Anjum, Paul Agbaje +2
Vision-language models (VLMs) demonstrate impressive zero-shot and few-shot learning capabilities, making them essential for several downstream tasks. However, fine-tuning these mo…
Toward Inherently Robust VLMs Against Visual Perception Attacks
Pedram MohajerAnsari, Amir Salarpour, Michael Kühr +6
Autonomous vehicles rely on deep neural networks (DNNs) for traffic sign recognition, lane centering, and vehicle detection, yet these models are vulnerable to attacks that induce…
Discovering New Shadow Patterns for Black-Box Attacks on Lane Detection of Autonomous Vehicles
Pedram MohajerAnsari, Amir Salarpour, Jan de Voor +6
We present a novel physical-world attack on autonomous vehicle (AV) lane detection systems that leverages negative shadows -- bright, lane-like patterns projected by passively redi…