Large Language Models (LLMs) present massive inherent knowledge and superior semantic comprehension capability, which have revolutionized various tasks in natural language processing. Despite their success, a critical...
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Nationwide in today's day to life the fundamental root causes of deaths and hospitalization is heart diseases which will put enormous economic burden on health care system and on the Human life. Prediction at earl...
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In this paper, a novel type of haptic human-machine interaction was presented to realize teleoperation. The system, consisting of 5 degrees of freedom (DOF) manipulator arm, a gripper and the virtual reality(VR) heads...
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Antimicrobial resistance (AMR) is one of the significant problems in the health sector and requires resources to create and develop accurate forecasting systems capable of recognizing resistant microbes and their trea...
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Approximate computing effectively impacts low-power VLSI circuits by reducing circuit overhead. It introduces minimal error in the output, which does not significantly affect the application. This paper proposes an ap...
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Effectively estimating numerous free parameters in large-scale biophysical neural network models based on sparse biological functional data is a formidable task. In this paper, we propose a simple yet efficient parame...
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It affords an overview latest, the modern-day inside the field of modern-day clinical picture segmentation, after which highlights the gain of trendy CNNs in it. The paper then describes today's CNNs’ fundamental...
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Domain transfer learning is a powerful device for clinical image Segmentation duties. It involves transferring information from a source domain to a goal area so that related tasks on those domains can be advantageous...
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Massive knowledge graphs (KGs) are increasingly significant in modern information systems. Previous research on knowledge graph completion must gather sufficient training instances for new introduced relations in orde...
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Scene text recognition (STR) is a challenging task that aims to automatically localize and recognize text in varied natural scenes. Although the performance of STR methods has been significantly improved, the STR prob...
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