In our usual life, data is all around us, everywhere we look! Now a days every individuals and organizations continue to generate, store, and share vast amounts of data and as a result the role of cloud storage becomes important to us. In the context of&...

Generating accurate SQL from natural language questions (text-to-SQL) is a longstanding challenge due to the complexities involved in understanding user queries, comprehending database schemas, and generating SQL statements. Traditional text-to-SQL systems have utilized human-engineered solutions and&#x...

With the rapid increase in digital images, it has become essential to have advanced systems to find specific images quickly from large collections. Traditional methods that depend on text descriptions often fail because tagging images manually is time-consuming and subjective. T...

In the bounded quantum storage model (BQSM), it is possible to realize oblivious transfer (OT) non-interactively. However, existing schemes are non-interactive only when the erasure rate is low. Quantum communication, even over short distances, is subject to relatively high erasure&#...

The role of embeddable cryptographic processors in revolutionizing defense communications for the Indian Navy bears immense significance. These processors serve as catalysts for a diverse range of novel applications critical to naval operations, encompassing tailored smartphones and robust...

In this work, we revisit Yao’s [Yao82] celebrated 1982 question concerning the collaborative computation of integer functions by a set of n parties, each initially possessing only their respective inputs. The challenge is to compute an integer function without revealing individual...

Owing to its adaptability in cryptographic protocols and possible defence against quantum attacks, lattice-based cryptography has become a very attractive topic. This survey explores the fundamental hard problems in lattice theory, such as the Shortest Vector Problem (SVP), the Close...

The potential of distributed ledger technologies, such as blockchain, to create responsible and transparent linkages across a range of application domains has garnered a lot of interest. These methods build redundant networks via hash functions, digital signatures, and asymmetric cry...

In this paper our main objective is to make a robust malware detector system by enhancing it’s ability to detect malicious applications. Machine learning based model has been used to detect or classify malware and benign samples, while the malware attackers have strong...

This thesis conducts a comprehensive security analysis of cryptographic primitives within the context of blockchain technology, focusing on MD5, Elliptic Curve Cryptography (ECC), and digital signatures. The first objective was to evaluate the security of MD5. The analysis revealed &...

This thesis contains three chapters on industrial organization, covering two distinct topics. Chapters 1 and 2 examine the impact of firm owner's corruption on the organization, while Chapter 3 analyzes the market dynamics of a two-sided newspaper market.\medskip The first&#...

Abstract

Abstract

Scene text detection is crucial for numerous applications, including autonomous driving and assistive technology for visually impaired individuals. This project leverages various versions of the You Only Look Once (YOLO) model to achieve efficient and accurate text detection in natur...

Alzheimer’s disease is a neurodegenerative disease that affects a multitude of people globally. It usually affects people of 60 yrs and older causing changes in the anatomy of the brain.Subjects diagnosed with Alzheimer’s disease often gets to live for 5-10 yrs.This makes&#...

In a crowdsourcing environment, judgment analysis involves gathering opinions from a diverse online crowd to reach a consensus. Traditional methods work onlywhenall opinions are available fromthe start. Our goal is to develop amethod for judgment analysis that works as opinions ...

Deep learning methods have significantly reduced the difficulties related to multi-oriented text detection in recent scene text detection advances. The restrictions of conventional text representations, like horizontal boxes, rotated rectangles, or quadrangles, make it difficult to recognize&...

Deep neural networks often struggle with heavily class-imbalanced training datasets. Recently, two-stage methods have been developed to separate representation learning from classifier learning, aiming to enhance performance. However, the crucial issue of miscalibration remains. To tackle this,...

Deep neural networks (DNNs) have shown exceptionally good performance in a variety of activities by using correctly labelled and ’good’ training datasets. These remarkable results, however, are mostly observed with datasets that are carefully controlled and precisely structured. Conversel...