Mobile banking has huge potentials to promote financial inclusions, especially in the rural areas. However, the adoptions in these areas are hampered by factors relating to security, misunderstanding, limitation in te...
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With the continuous increase in vehicle numbers, traffic violations have become prevalent. Traditional detection approaches are often labor-intensive and constrained by geographical and temporal limitations. This pape...
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Early diagnosis of such maladies can avoid crop diseases and increase agricultural yield. We attempt to propose deep learning-based approach for the classification of diseases in an apple crop using the New Plant illn...
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The increasing frequency of space launch missions underscores their vital role in national security and technological advancement. These missions involve a complex set of tasks, each reliant on limited resources and s...
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This paper introduces an innovative method for improving solar power prediction accuracy by integrating realtime weather forecasting, advanced machine learning techniques, and hybrid modelling frameworks. The proposed...
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Lung cancer continues to be a leading cause of death, and hence there is a significant need for early detection to improve survival rates. This current research addresses some loopholes existing in the current diagnos...
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Currently, deep learning-based object detection algorithms can rapidly and accurately locate vehicles and pedestrians under normal conditions. However, in low-light environments, the detection accuracy of these algori...
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The ability to discern between text produced by artificial intelligence (AI) and that created by humans has become a crucial challenge in domains including academia, media, and digital communications due to the increa...
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Heart attacks and hypertension are two cardiovascular disease risk factors that have a major impact on the microvascular system's structure and function. Fundus camera images can detect abnormalities in retinal bl...
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As edge-based decisions continue to grow in demand, organizations are increasingly seeking user data, raising privacy concerns. Federated learning (FL) addresses this problem but is typically dependent on computationa...
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