[ad_1] Introduction Quantum-inspired optimization has emerged as a promising approach for solving complex optimization problems in various domains. In the context of network resource allocation, the efficient utilization of resources is crucial for ensuring high…
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[ad_1] Introduction Multi-modal learning for visual-textual alignment is a rapidly growing research area that aims to bridge the gap between different modalities, such as images and text, in order to improve the performance of various…
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[ad_1] Introduction: Zero-shot learning for semantic segmentation is a cutting-edge research topic in the field of computer vision, with the potential to revolutionize the way we approach image segmentation tasks. Traditional semantic segmentation methods require…
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[ad_1] Introduction In recent years, there has been a growing interest in the development of multi-robot systems for various applications such as search and rescue, surveillance, and environmental monitoring. However, coordinating multiple robots to work…
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[ad_1] Introduction Quantum key distribution (QKD) is a cutting-edge technology that utilizes principles of quantum mechanics to establish secure communication channels. With the increasing reliance on digital systems in industrial control systems, the need for…
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[ad_1] Introduction Neuromorphic computing is a rapidly advancing field that seeks to mimic the biological neural networks of the brain in order to create more efficient and adaptable computing systems. This technology has the potential…
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[ad_1] Introduction With the increasing use of cloud computing and outsourced data processing, the need for secure methods of handling sensitive data has become more crucial. Homomorphic encryption is a promising solution that allows for…
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[ad_1] Introduction Serverless computing has emerged as a promising solution for executing scientific workflows in a cost-effective and scalable manner. By abstracting away the infrastructure management, serverless computing enables researchers to focus on developing and…
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[ad_1] Introduction Generative adversarial networks (GANs) have gained significant attention in the field of artificial intelligence and computer vision for their ability to generate realistic images. In recent years, GANs have been successfully applied to…
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[ad_1] Thesis Overview: In recent years, deep learning models have shown remarkable success in various applications such as image recognition, speech recognition, and natural language processing. However, the widespread adoption of these models raises concerns…
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