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Kittler, \u201cThe ham10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions,\u201d arXiv preprint arXiv:1803.10417, 2018."},{"key":"pone.0234352.ref034","article-title":"Skin lesion analysis toward melanoma detection: A challenge at the 2017 international symposium on biomedical imaging (isbi)","author":"N. Codella","year":"2017","journal-title":"hosted by the international skin imaging collaboration (isic)"},{"issue":"10","key":"pone.0234352.ref035","doi-asserted-by":"crossref","first-page":"1605","DOI":"10.1109\/5.58346","article-title":"Entropy nets: from decision trees to neural networks","volume":"78","author":"I.K. Sethi","year":"1990","journal-title":"Proc. IEEE"},{"key":"pone.0234352.ref036","volume-title":"Classification and regression trees","author":"L. Breiman","year":"1984"},{"issue":"2","key":"pone.0234352.ref037","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"D. G. Lowe","year":"2004","journal-title":"IJCV"},{"key":"pone.0234352.ref038","unstructured":"D.S. Bloomberg, G.E. Kopec, and L. Dasari, \u201cMeasuring document image skew and orientation,\u201d Document Recognition II (SPIE vol. 2422), San Jose, CA, February 6-7, 302-316, 1995."},{"key":"pone.0234352.ref039","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1109\/TIT.1962.1057692","article-title":"Visual pattern recognition by moment invariants","volume":"8","author":"M.K. Hu","year":"1962","journal-title":"IRE Transactions on Information Theory"},{"key":"pone.0234352.ref040","volume-title":"Content-based microscopic image analysis","author":"C. Li","year":"2016"},{"key":"pone.0234352.ref041","unstructured":"C.I.E., \u201cRecommendations on uniform color spaces, color difference equations, psychometric color terms,\u201d Supplement No.2 to CIE publication No.15 (E.-1.3.1) 1971\/(TC-1.3.), 1978."},{"key":"pone.0234352.ref042","volume-title":"Decision making processes in pattern recognition","author":"G. S. Sebestyen","year":"1962"},{"key":"pone.0234352.ref043","unstructured":"J. MacQueen, \u201cSome methods of classification and analysis of multivariate observations,\u201d In L. M. Le Cam & J. Neyman (Eds.), Proceedings of the fifth Berkeley symposium on mathematical statistics and probability (Vol. 1, pp. 281-297). Berkeley, CA: University of California Press, 1967."},{"key":"pone.0234352.ref044","doi-asserted-by":"crossref","unstructured":"P.J. Groenen, U. Kaymak, and J. van Rosmalen, \u201cFuzzy clustering with minkowski distance functions,\u201d In Advances in Fuzzy Clustering and its Applications (eds J. 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Ye, \u201cA deep learning based approach to skin lesion border extraction with a novel edge detector in dermoscopy images,\u201d The International Joint Conference on Neural Networks, 2019.","DOI":"10.1109\/IJCNN.2019.8852134"},{"key":"pone.0234352.ref050","doi-asserted-by":"crossref","unstructured":"A. Ali, J. Li, and T. 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