5 citations · 9 across the 11 of their papers we have counts for
12 papers
Q-Capsule: A Localized Capsule-Based Quantum Neural Architecture for Barren Plateau Mitigation
Awal Ahmed Fime, Tasfia Zaman Samiha, Saika Zaman +4
Variational quantum algorithms are often limited by barren plateaus: gradients vanish as circuit size and depth increase, making quantum neural networks difficult to train. We prop…
Adaptive and Robust Data Poisoning Detection and Sanitization in Wearable IoT Systems using Large Language Models
W. K. M Mithsara, Ning Yang, Ahmed Imteaj +2
The widespread integration of wearable sensing devices in Internet of Things (IoT) ecosystems, particularly in healthcare, smart homes, and industrial applications, has required ro…
Digital Forensic Investigation of the ChatGPT Windows Application
Malithi Wanniarachchi Kankanamge, Nick McKenna, Santiago Carmona +3
The ChatGPT Windows application offers better user interaction in the Windows operating system (OS) by enhancing productivity and streamlining the workflow of ChatGPT's utilization…
Distributed LLMs and Multimodal Large Language Models: A Survey on Advances, Challenges, and Future Directions
Hadi Amini, Md Jueal Mia, Yasaman Saadati +6
Language models (LMs) are machine learning models designed to predict linguistic patterns by estimating the probability of word sequences based on large-scale datasets, such as tex…
Exploring Audio Editing Features as User-Centric Privacy Defenses Against Large Language Model(LLM) Based Emotion Inference Attacks
Mohd. Farhan Israk Soumik, W. K. M. Mithsara, Abdur R. Shahid +1
The rapid proliferation of speech-enabled technologies, including virtual assistants, video conferencing platforms, and wearable devices, has raised significant privacy concerns, p…
TriplePlay: Enhancing Federated Learning with CLIP for Non-IID Data and Resource Efficiency
Ahmed Imteaj, Md Zarif Hossain, Saika Zaman +1
The rapid advancement and increasing complexity of pretrained models, exemplified by CLIP, offer significant opportunities as well as challenges for Federated Learning (FL), a crit…
Securing Vision-Language Models with a Robust Encoder Against Jailbreak and Adversarial Attacks
Md Zarif Hossain, Ahmed Imteaj
Large Vision-Language Models (LVLMs), trained on multimodal big datasets, have significantly advanced AI by excelling in vision-language tasks. However, these models remain vulnera…
Sim-CLIP: Unsupervised Siamese Adversarial Fine-Tuning for Robust and Semantically-Rich Vision-Language Models
Md Zarif Hossain, Ahmed Imteaj
Vision-Language Models (VLMs) rely heavily on pretrained vision encoders to support downstream tasks such as image captioning, visual question answering, and zero-shot classificati…
Towards Sustainable SecureML: Quantifying Carbon Footprint of Adversarial Machine Learning
Syed Mhamudul Hasan, Abdur R. Shahid, Ahmed Imteaj
The widespread adoption of machine learning (ML) across various industries has raised sustainability concerns due to its substantial energy usage and carbon emissions. This issue b…
FedAVO: Improving Communication Efficiency in Federated Learning with African Vultures Optimizer
Md Zarif Hossain, Ahmed Imteaj
Federated Learning (FL), a distributed machine learning technique has recently experienced tremendous growth in popularity due to its emphasis on user data privacy. However, the di…
An enhanced method of initial cluster center selection for K-means algorithm
Zillur Rahman, Md. Sabir Hossain, Mohammad Hasan +1
Clustering is one of the widely used techniques to find out patterns from a dataset that can be applied in different applications or analyses. K-means, the most popular and simple…
Label Flipping Data Poisoning Attack Against Wearable Human Activity Recognition System
Abdur R. Shahid, Ahmed Imteaj, Peter Y. Wu +2
Human Activity Recognition (HAR) is a problem of interpreting sensor data to human movement using an efficient machine learning (ML) approach. The HAR systems rely on data from unt…