Food wastage is one of the most persistent challenges of the food industry, leading to immense economic and environmental losses. The root cause of such a problem lies in mistaken demand prediction, which means overpr...
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Accurate flood risk prediction is critical for disaster management, particularly given the increased unpredictability of weather patterns caused by climate change. This work applies to a 1-day-ahead flood forecast mod...
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In today’s workplace, desk employees often spend long hours sitting in front of computers, leading to issues such as poor posture, back pain, neck strain, and other musculoskeletal problems. This research presents a ...
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Fine-tuning large language models (LLMs) for domain specific tasks is often an expensive resource intensive procedure requiring large computing and memory resources. In this paper, We introduce finetuned-leetcode-Code...
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Predicting customer purchase intent is crucial for modern businesses in order to improve engagement, refine marketing strategies, and increase revenue. Conventional rule-based systems encounter difficulties with dynam...
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Assessment of student responses during viva examinations presents challenges in terms of consistency, objectivity, and efficiency. Traditional methods rely on manual evaluation, which can be lengthy and prone to human...
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The swift progression of deepfake-generating technologies has elicited much apprehension about their potential misuse in digital media, necessitating the development of efficient detection methods. This research aims ...
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With the expansion of social media and advanced stages, the spread of fake news has ended up a noteworthy societal issue. This paper presents a comprehensive outline of machine learning strategies utilized for the det...
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We conduct an extensive study on deep learning-based spectrum sharing to resolve dynamic resource allocation in 6G cognitive radio networks in this paper. The approach uses modern machine learning models to optimize s...
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As biometric systems become increasingly relied on secure authentication, concerns about their susceptibility to Face Presentation Attacks (FPAs) have intensified. This paper introduces a framework for detection of im...
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