Titlebook: Recent Trends in Image Processing and Pattern Recognition; 6th International Co KC Santosh,Aaisha Makkar,Ravindra Hegadi Conference proceed

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A Stack Ensemble Approach for Early Alzheimer Classification Using Machine Learning Algorithms research gap by conducting a comprehensive and meticulous series of experiments. A comprehensive examination of data obtained from sophisticated neuroimaging technologies is performed by utilising a wide range of machine learning models, such as Logistic Regression, Naive Bayes, Neural Networks, Ra

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Realistic Skin Image Data Generation Leveraging Conditional GAN and Classification Using Deep CNNa significant boost in classification accuracy, elevating it from 0.7532 to 0.8734, complemented by precision 0.91, recall 0.878 F1-score 0.8936. These promising results underscore the advantages of deploying GANs for data augmentation in biomedical image classification tasks, when compared with wel

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Exploring Imaging Biomarkers for Early Detection of Alzheimer’s Disease Using Deep Learning: A Comprr scans. It also explains the potential benefits of using emerging retinal scans for enhanced detection. It also explains various deep learning techniques that harness both local and global features to enhance accuracy by utilizing extensive scan data.

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Rohini A. Bhusnurmath,Shivaleela Betagerid scholars and policy makers have a tremendous desire to do research on this region from a variety of perspectives (Zahra, 2011). Yet, it is probably one of the least researched corners of the world in terms of quantitative analyses (Genc et al., 2011). When one focuses on the contribution of studie

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