Research Intern – Deep Learning, Few-Shot Skin Cancer Classification
ImageClassification
I conducted deep learning research on few-shot skin cancer classification using medical images. My primary task involved training and evaluating models with limited labeled data to improve diagnostic accuracy. This experience focused on building and testing AI models for image classification in a healthcare context.
• Applied CNN and transfer learning techniques to medical image datasets.
• Labeled and organized few-shot image samples for model input and testing.
• Optimized classification tasks with precise label assignments for diagnosis support.
• Evaluated and reported model results relevant to labeled data performance.
I conducted deep learning research on few-shot skin cancer classification using medical images. My primary task involved training and evaluating models with limited labeled data to improve diagnostic accuracy. This experience focused on building and testing AI models for image classification in a healthcare context. • Applied CNN and transfer learning techniques to medical image datasets. • Labeled and organized few-shot image samples for model input and testing. • Optimized classification tasks with precise label assignments for diagnosis support. • Evaluated and reported model results relevant to labeled data performance.
2025 - 2025