[ad_1] Introduction: Generative adversarial networks (GANs) have gained significant attention in recent years for their ability to generate realistic images from text descriptions. In the field of text-to-image synthesis, GANs have shown promising results in…
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[ad_1] Introduction Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) have emerged as a powerful cryptographic tool for ensuring privacy and security in various applications. In the context of federated learning, where multiple parties collaborate to…
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[ad_1] Introduction In the era of big data and connected devices, federated learning has emerged as a promising approach to collaborative machine learning without compromising data privacy. Federated transfer learning extends the concept of federated…
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[ad_1] Introduction Quantum computing is a rapidly evolving field that has the potential to revolutionize the way we process and analyze data. Quantum machine learning is an emerging area of research that combines principles of…
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[ad_1] Introduction Decentralization has been a hot topic in recent years, with many industries exploring ways to shift away from centralized systems towards more distributed and transparent alternatives. This shift has also been seen in…
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[ad_1] Introduction Quantum-inspired optimization algorithms have gained significant attention in recent years due to their ability to solve complex optimization problems efficiently. One such problem that can benefit from quantum-inspired optimization is the vehicle routing…
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[ad_1] Introduction Emotion recognition is a crucial aspect of human interaction and communication. Being able to accurately identify and understand the emotions of others can lead to better relationships and more effective communication. In recent…
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[ad_1] Introduction Privacy-preserving machine learning has become a critical research area in the era of big data and artificial intelligence. As organizations collect and analyze vast amounts of sensitive data for various purposes, the need…
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[ad_1] Introduction Chapter 1: Introduction 1.1 Introduction 1.2 Background of study 1.3 Problem Statement 1.4 Objective of study 1.5 Limitation of study 1.6 Scope of study 1.7 Significance of study 1.8 Structure of the Thesis…
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[ad_1] Introduction Transfer learning has emerged as a powerful tool in machine learning, allowing models trained on one task or domain to be adapted to new, related tasks or domains. In the field of natural…
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