With the advent of hybrid CPUs integrated with GPUs, achieving peak performance and energy efficiency necessitates the effective utilization of all available resources. This project explores workload partitioning strategies ...
My work extends previous work on proactive spatial prediction of radio environments for spectrum sharing by integrating it into a distributed Federated Learning (FL) framework. In this enhanced version of the Federated ...
Generating novel recipes within specific cuisine constraints is a challenging task that combines creativity with cultural authenticity. This study explores the capabilities of fine-tuned large lan guage models (LLMs), ...
This project presents navX, a comprehensive career guidance platform in the form of a website, designed to address the gaps in current systems by providing personalized and accessible career advice to students and parents, ...
Accurate prediction and tracking of ocean wave dynamics especially near the beach side are important for enhancing the safety and experience of surfers. This study presents a deep learning based approach that uses computer ...
This report explores advancements and methodologies in the development and fine-tuning of large language models (LLMs) and their integration into knowledge-intensive tasks. It em phasizes the role of retrieval-augmented ...
Image Based Visual Servoing (IBVS) and autonomous navigation in robots often rely on phys ical markers for fast detection and estimation of pose and orientation. However, in real-world scenarios, the use of fiducial markers ...
One of the biggest challenges when it comes to retrieving information from diversified and complex datasets, such as PDFs, is their unstructured nature and the possibility of re ceiving irrelevant or incorrect responses. ...
This study explores potential improvement in the efficiency of traditional Magnetic Tunnel Junctions (MTJ) through utilisation of an altered double MTJ with a non-magnetic metalllic spacer (tungsten) for resonant tunneling. ...
WiFi signals have become pivotal in sensing applications by leveraging Channel State Informa tion (CSI). WiImg, a novel system, utilizes Generative Adversarial Networks (GAN) for image inpainting to perform WiFi sensing ...
In the field of deception analysis, controlled dialogue summarization plays a critical role in dis tilling key information from witness testimonies. This project aims to develop a summarization framework for interrogations ...
In an era where personal safety remains a paramount concern, especially among vulnerable groups such as women, children, and the elderly, innovative solutions are essential to address the escalating risks of stalking, ...
The increasing complexity of codebases demands advanced methods for automated code gener ation and repository understanding. This project explores the synergistic application of large language models (LLMs), knowledge ...
Large Language Models (LLMs) have revolutionized natural language processing applications, but their computational and memory demands often overshadow their utility in resource-constrained scenarios, particularly in ...
Antimicrobial resistance (AMR) is one of the most significant global health threats of the 21st century, driven by the overuse and misuse of antibiotics and the lack of effective surveillance systems. This study leverages ...
Scene transitions are integral to video editing, enabling seamless storytelling by connecting dis tinct video segments into a cohesive visual narrative. Despite advancements in video editing tools, automated generation of ...
The rapid adoption of Android devices has been paralleled by a significant rise in Android malware, leveraging sophisticated techniques to evade detection and execute malicious activi ties. This research investigates the ...
This study aims to understand the feasibility of a stress detection model through a smartwatch using the physiological data collected for lab and real-life settings. Wearable devices such as smartwatches have the potential ...
This project focuses on the development and evaluation of a student model for audio deepfake detection, leveraging a single teacher model from a selection of advanced architectures, including XLSR, Facebook MMS, X-vector, ...
Distributed machine learning (ML) workloads, particularly the training of deep neural networks (DNNs) and large language models (LLMs), rely heavily on efficient network communication to achieve scalability. However, network ...