Das, A., & Sabut, S. K. (2016). Kernelized Fuzzy C-means Clustering with Adaptive Thresholding for Segmenting Liver Tumors. Procedia Computer Science, 92, 389-395. https://doi.org/10.1016/j.procs.2016.07.395
ISO-690 (author-date, English)DAS, Amita und SABUT, Sukanta Kumar, 2016. Kernelized Fuzzy C-means Clustering with Adaptive Thresholding for Segmenting Liver Tumors. Procedia Computer Science. 15 August 2016. Vol. 92, , p. 389-395. DOI 10.1016/j.procs.2016.07.395.
Modern Language Association 9th editionDas, A., und S. K. Sabut. „Kernelized Fuzzy C-Means Clustering With Adaptive Thresholding for Segmenting Liver Tumors.“. Procedia Computer Science, Bd. 92, August 2016, S. 389-95, https://doi.org/10.1016/j.procs.2016.07.395.
Mohr Siebeck - Recht (Deutsch - Österreich)Das, Amita/Sabut, Sukanta Kumar: Kernelized Fuzzy C-means Clustering with Adaptive Thresholding for Segmenting Liver Tumors., Procedia Computer Science 2016, 389-395.
Emerald - HarvardDas, A. und Sabut, S.K. (2016), „Kernelized Fuzzy C-means Clustering with Adaptive Thresholding for Segmenting Liver Tumors.“, Procedia Computer Science, Vol. 92, S. 389-395.