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IEEE/ICACT20250193 Slide.13        [Big Slide]       [YouTube]	Oral Presentation
	Conclusion This study showcases the effectiveness of an ensemble learning approach using transfer learning models for accurate skin cancer classification. By leveraging pre-trained weights, fine-tuning models, and applying a consensus-based ensemble method, the system achieves high accuracy in distinguishing malignant and benign lesions. The approach offers a non-invasive, reliable diagnostic tool, highlighting the potential of AI-driven solutions to support early skin cancer detection and assist healthcare professionals in dermatology.

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