Melanoma Classification Through Transfer Learning by the Analysis of Skin Lesion Images

Author:

Balabantaray Bunil Kumar,Chakravarty Rommel,Panda Akash Kumar,Nayak Rajashree

Publisher

Springer Singapore

Reference20 articles.

1. Gutman D, Codella NCF, Celebi E, Helba B, Marchetti M, Mishra N, Halpern A (2016) Skin lesion analysis toward melanoma detection: a challenge at the international symposium on biomedical imaging (ISBI) 2016, hosted by the International Skin Imaging Collaboration (ISIC). arXiv:1605.01397v1 [cs.CV] 4 May 2016

2. Siegel RL, Miller KD, Jemal A (2020) Cancer statistics, 2020. CA Cancer J Clin 70:7–30

3. Melanoma—symptoms and causes. https://www.mayoclinic.org/diseases-conditions/melanoma/symptoms-causes/syc-20374884

4. Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, Thrun S (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nature 542:115

5. He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: The IEEE conference on computer vision and pattern recognition (CVPR), pp 770–778

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A survey, review, and future trends of skin lesion segmentation and classification;Computers in Biology and Medicine;2023-03

2. Machine Learning Assisted Early Diagnosis of Skin Cancer;2022 IEEE International Conference on Current Development in Engineering and Technology (CCET);2022-12-23

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