Software Defined Networking (SDN) has brought about a revolutionary shift in network management and control. The driving force behind SDN's development is the need for enhanced network programmability and scalabil...
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The rapid advancement of deep learning has made major advancements surveillance applications, yet detecting targets remains challenging due to size variations and environmental factors. In this paper, we integrated th...
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Heart failure is a prevalent cardiovascular disease with significant global mortality rates. Accurate prediction methods are imperative for predicting cardiovascular disease and identifying individuals at risk of adve...
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In the rapidly evolving landscape of computer vision, image captioning has emerged as a challenging task. This report explores the techniques involved in image captioning using deep learning techniques, especially the...
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Data is valuable asset for organizations but it cannot be used directly for business decision making. It needs to be processed in a form that is easily understandable and can to be used by decision makers. The databas...
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In recent years, the emergence of the Internet and E-commerce has steered significant growth in digital transactions. Businesses today need mobile wallets, credit and debit cards, and e-cash to digitize payments. Digi...
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In our day-to-day lives, monitoring health regularly is essential to ensure the body functions well under various conditions. This paper outlines the development of a smart health monitoring wearable device utilizing ...
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Compiler optimization significantly impacts algorithm performance, whether it may be graph-based, parallel computing workloads and more. Understanding how these algorithms' performance varies under different optim...
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Autonomous vehicles (AVs) are susceptible to cyberattacks due to their reliance on vehicle-to-everything (V2X) communication. This research proposes a Gradient Boosting-based intrusion detection system to safeguard AV...
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Oil spills present a critical hazard in oceans, requiring advanced monitoring systems to rapidly detect and contain environmental damage. This work proposes a deep learning approach combining a UNet encoder-decoder ar...
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