In this project, we ventured into computational gastronomy to craft AI-generated recipes that embody diverse regional cooking styles. Our methodology initially centered on a novel tokenization approach, using the GPT-2-based ...

This thesis explores the dynamics of online algorithms, with a focus on the List Update Problem in online optimization. Our study revolves around the analysis of various algorithmic strategies, under the frameworks of ...

Edge computing has emerged as a promising paradigm for meeting the requirements of resourceintensive applications by processing data at the network edge. The aim of our project is to optimise the end to end tail latency ...

In response to India’s National Digital Health Mission (NDHM), TavLabs has innovatively enhanced its PHR platform by integrating a Mental Health Integration feature, designed to support and prioritize mental well-being. ...

Image-Text Retrieval (ITR) is the task of retrieving an image from a corresponding textual description and/or a textual description from the corresponding image. Person Re-Identification (Person Re-ID) is a downstream task ...

With the introduction of the EU’s GDPR in 2017, lawmakers have emphasized the importance of algorithmic decisions being explainable to people affected by those decisions. This has led to a major focus being put on Explainable ...

This study addresses the critical issue of antimicrobial resistance (AMR) in Escherichia coli through machine learning techniques. Our methodology includes using already available E.coli strains that are susceptible and ...

In recent years, the censorship measures taken by various countries have introduced large-scale and sophisticated apparatuses to prevent citizens from accessing the internet freely. Numerous efforts have been made in this ...

In an era marked by unprecedented data growth and pervasive digital influence, ensuring model privacy is imperative as machine learning models gain prominence in diverse domains like healthcare, finance, and business. ...

Neurodegenerative diseases pose a significant global health challenge, necessitating innovative approaches for drug discovery. This study explores the application of recurrent neural networks (RNNs) in the generation of ...