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ARL-CNN50 기반 피부병변 분류진단
ARL-CNN50 for Skin Lesion Classification
조광지 ( Guangzhi Zhao ) , 웬트리찬훙응 ( Nguyen Tri Chan Hung ) , 이효종 ( Hyo Jong Lee )
UCI I410-ECN-0102-2023-500-000818038
이 자료는 4페이지 이하의 자료입니다.

With the advent of the era of artificial intelligence, more and more fields have begun to use artificial intelligence technology, especially the medical field. Cancer is one of the biggest problems in the medical field. [1] If it can be detected early and treated early, the possibility of cure will be greatly increased. Malignant skin cancer, as one of the types of cancer with the highest fatality rate in recent years has problems such as relying on the experience of doctors and being unable to be detected and detected in time. Therefore, if artificial intelligence technology can be used to help doctors in early detection of skin cancer, or to allow everyone to detect skin lesions or spots anytime, anywhere, it will have great practical significance. In this paper we used attention residual learning convolutional neural network (ARL-CNN) model [2] to classify skin cancer pictures.

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