Ensemble of Convolutional Neural Networks for Dermoscopic Images Classification

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Barata, C., Celebi, M., Marques, J.: Improving Dermoscopy Image Classification Using Color Constancy. IEEE Journal of Biomedical and Health Informatics 19(3), 1146–1152 (2015)

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Esteva, A., Kuprel, B., Novoa, R., Ko, J., Swetter, S., Blau, H., Thrun, S.: Dermatologist-Level Classification of Skin Cancer with Deep Neural Networks. Nature 542(7639), 115 (2017)

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Kumar, A., Kim, J., Lyndon, D., Fulham, M., Feng, D.: An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification. IEEE J. of Biomed. and Health Inf. 21(1), 31–40 (2017)

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Codella, N., Gutman, D., Celebi, M., Helba, B., Marchetti, M., Dusza, S., Kalloo, A., Liopyris, K., Mishra, N., Kittler, H., et al.: Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC). In: IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018). pp. 168–172. IEEE (2018)

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Tschandl, P., Rosendahl, C., Kittler, H.: The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions. Sci. Data 5, 180161 (2018)