Melanoma Detection and Classification based on Dermoscopic Images using Deep Learning Architectures-A Study DOI

Nancy Emymal Samuel,

J. Anitha

2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA), Год журнала: 2022, Номер 392, С. 993 - 1000

Опубликована: Сен. 21, 2022

Skin cancer is the abnormal growth of skin cells. Melanoma very dangerous form cancer, it spreads to neighboring tissue rapidly. Thus early detection melanoma required. Here we examine existing approaches automatic identification and categorization in dermoscopic pictures, emphasizing major features main discrepancies between methodologies used. The goal highlight benefits drawbacks various approaches. Unlike other studies that just explain evaluate different qualitatively, this one includes a quantitative comparison. Using distinct lesion databases, performance numerous algorithms compared. accuracy, specificity, sensitivity results are presented.

Язык: Английский

Melanoma Detection and Classification based on Dermoscopic Images using Deep Learning Architectures-A Study DOI

Nancy Emymal Samuel,

J. Anitha

2022 4th International Conference on Inventive Research in Computing Applications (ICIRCA), Год журнала: 2022, Номер 392, С. 993 - 1000

Опубликована: Сен. 21, 2022

Skin cancer is the abnormal growth of skin cells. Melanoma very dangerous form cancer, it spreads to neighboring tissue rapidly. Thus early detection melanoma required. Here we examine existing approaches automatic identification and categorization in dermoscopic pictures, emphasizing major features main discrepancies between methodologies used. The goal highlight benefits drawbacks various approaches. Unlike other studies that just explain evaluate different qualitatively, this one includes a quantitative comparison. Using distinct lesion databases, performance numerous algorithms compared. accuracy, specificity, sensitivity results are presented.

Язык: Английский

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