An efficient skin cancer detection and classification performance using adaptive residual DenseNet with attention mechanism

Key Points

• To improve the detection and classification performance of skin cancer using adaptive residual DenseNet with an attention mechanism.
• Utilized adaptive residual DenseNet architecture for image analysis.
• Implemented an attention mechanism to enhance feature extraction.
• Evaluated the model's performance on skin cancer datasets.
• Achieved higher classification accuracy compared to traditional methods.
• Demonstrated improved detection rates for various skin cancer types.
• Indicated reduced false positive and false negative rates.