Titlebook: High Performance Computing, Smart Devices and Networks; Select Proceedings o Ruchika Malhotra,L. Sumalatha,Naresh Babu Muppalan Conference

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Comparative Analysis of CNN Models with Vision Transformer on Lung Infection Classification,d analyzing lung infections by using InceptionV3, ResNet50, VGG16, InceptionResNet, and Vision Transformer. Each model is evaluated on the basis of mean accuracy error (MAE), binary accuracy, and loss. Among all the models, InceptionResNet has obtained a best accuracy of 93.33%. This study signifies

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,Classification of Alzheimer’s Disease Using Stacking-Based Ensemble and Transfer Learning,different stages. The approach produces efficient and accurate results and is designed to encourage the implementation of deep learning in day-to-day medicine without the need for much human involvement. In the proposed method, we use transfer learning to employ three pre-trained deep learning model

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Heart Device for Expectation of Coronary Illness Utilizing Internet of Things,e effect of pressure chemicals on hidden heart sicknesses. Numerous wearable innovations screen commonplace heart working pointers like circulatory strain, glucose level, blood oxygen immersion, and ECG. The proposed framework might gather the fundamental information while barring commotion unsettli

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An Extensive Study of Frequent Mining Algorithms for Colossal Patterns,mall and mid-sized patterns aren’t mined, mining algorithms for enormous patterns run faster. In this work, an extensive study of colossal patterns, existing mining algorithms with its drawback is mentioned. The definitions of FPM, high utility mining and relation of colossal patterns with others ar

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commonsense

Ensemble Model Detection of COVID-19 from Chest X-Ray Images,d models’ performance is estimated in terms of accuracy, precision, recall, and f1-score parameters and achieved better results for detection purpose. Hence, the proposed model is a promising diagnostic tool for accurate screening of COVID-19 disease.

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The Development of Advanced Deep Learning-Based EoR Signal Separation Techniques, results show that compared with the traditional methods including polynomial fitting and continuous wavelet transform, the EoR signals detected by the proposed deep learning model have better quantitative evaluation indexes of SNR and Pearson correlation coefficient. This property provides a new way to explore the research field of EoR.

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ectropion

Conference proceedings 2024he reader an up-to-date picture of the state-of-the-art connection between computational intelligence, machine learning, and IoT. The papers in this volume are peer-reviewed by experts in related areas. The book will serve as a valuable reference resource for academics and researchers across the globe..