Leveraging YOLOv9 for Enhanced Skin Cancer Detection: A Deep Learning Approach

In this paper, we present a YOLOv9 based framework to detect, identify and classify skin cancer lesions. A real-time processing capabilities that aim to improve the mean average precision (mAP) scores while maintain a high processing speeds suitable for mobile health applications. The performance indicates that YOLOv9 not only achieves higher accuracy and efficiency in lesion detection but also demonstrates robustness against common image distortions such as hair and pigmentation.