Malaria Detection Using Transfer Learning Models

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This presentation explores advanced methods for malaria detection using transfer learning. It covers an overview of malaria, challenges faced, and highlights the use of ResNet50V2 and VGG19 models. Techniques, model architectures, and experimental methods are discussed, alongside accuracy trends and performance metrics. The key findings, clinical implications, and potential future research directions are summarized.