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Titlebook: Computer, Communication, and Signal Processing; 6th IFIP TC 5 Intern Erich J. Neuhold,Xavier Fernando,Aravindan Chandra Conference proceedi

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Conference proceedings 2022d in Chennai, India, in February 2022.*...The 21 full and 2 short papers presented in this volume were carefully reviewed and selected from 111 submissions. The papers are categorized into topical sub-headings: artificial intelligence and machine learning; Cyber security; and internet of things..*Th
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Conference proceedings 2022sions. The papers are categorized into topical sub-headings: artificial intelligence and machine learning; Cyber security; and internet of things..*The conference was held as a virtual event due to the COVID-19 pandemic. .
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The European Union and World Politicsn this work, the application of the attention mechanism helped to enhance the classification performance for binary and multiclass systems. A densenet with additive attention is implemented for softmax and sigmoid classification, increasing accuracy, recall, and F1-score.
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The Implications of the Rise of Chinaed different architectures with respect to COVID-19 diagnosis in the literature. This survey also briefs about quantifying metrics and the reported results are enumerated, also regulatory frameworks for public use of Artificial Intelligence (AI) in medical devices are comprehended.
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A Survey on DL Based Frameworks for COVID-19 Radiological Diagnosised different architectures with respect to COVID-19 diagnosis in the literature. This survey also briefs about quantifying metrics and the reported results are enumerated, also regulatory frameworks for public use of Artificial Intelligence (AI) in medical devices are comprehended.
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Fashion Image Classification Using Deep Convolution Neural Networkfication problem and to evaluate the performance of CNN’s Adam and RMSProp optimizer. The experiment was carried out using the Fashion-MNIST benchmark dataset. The suggested method has a test accuracy of 92.68%, compared to 91.86% in CNN using the softmax function and 92.22% in CNN utilizing batch normalization.
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