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Deep autoencoder-based fuzzy c-means for topic detection
Array, 2022 Topic detection is a process for determining topics from a collection of textual data. One of the topic detection methods is clustering based, which assumes that the centroids are topics.
Hendri Murfi +2 more
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Statistical and fuzzy clustering methods and their application to clustering provinces of Iraq based on agricultural products [PDF]
AUT Journal of Mathematics and Computing, 2020 The important approaches to statistical and fuzzy clustering are reviewed and compared, and their applications to an agricultural problem based on a real-world data are investigated.
Israa Atiyah, Seyed Mahmoud Taheri
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Residual-driven Fuzzy C-Means Clustering for Image Segmentation [PDF]
IEEE/CAA Journal of Automatica Sinica, 2020 In this paper, we elaborate on residual-driven Fuzzy C-Means (FCM) for image segmentation, which is the first approach that realizes accurate residual (noise/outliers) estimation and enables noise-free image to participate in clustering.
Cong Wang +3 more
semanticscholar +1 more source
Information Sciences, 2021 Although satellite images can provide more information about the earth’s surface in a relatively short time and over a large scale, they are affected by observation conditions and the accuracy of the image acquisition equipment. The objects on the images
D. Mai +3 more
semanticscholar +1 more source
Performance comparison of fuzzy and non-fuzzy classification methods
Egyptian Informatics Journal, 2016 In data clustering, partition based clustering algorithms are widely used clustering algorithms. Among various partition algorithms, fuzzy algorithms, Fuzzy c-Means (FCM), Gustafson–Kessel (GK) and non-fuzzy algorithm, k-means (KM) are most popular ...
B. Simhachalam, G. Ganesan
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Perbandingan Algoritma C-Means Clustering dan Fuzzy C-Means Clustering
Ultima Computing : Jurnal Sistem Komputer, 2019 Salah satu operasi di dalam analisis citra adalah segmentasi citra. Pada mulanya proses segmentasi dilakukan untuk memisahkan objek dari latar belakangnya, sehingga segmentasi merupakan bagian penting dalam pengenalan objek. Saat ini segmentasi sudah mengalami perkembangan yang sangat pesat, bukan hanya untuk tujuan pengenalan objek saja tetapi juga ...
Abi Kabisah Maulillah, Adhi Kusnadi
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Clustering models for hospitals in Jakarta using fuzzy c-means and k-means
Procedia Computer Science, 2023 After facing the COVID-19 pandemic, national and local governments in Indonesia realized a gap in the distribution of health care and human health practitioners.
Karli Eka Setiawan +3 more
semanticscholar +1 more source
IEEE Access, 2020 Due to the rapid development of information technology and network technology, there is a lot of data, but the phenomenon of lack of knowledge is becoming more and more serious.
Yuan Huang +4 more
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ComTech, 2023 The research aimed to use Fuzzy C-Means clustering in content-based document clustering to classify general websites based on their content. The data used were a table ranking of the most visited websites for Indonesia, taken from https://dataforseo.com ...
Sri Probo Aditiyo +2 more
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Superpixel-Based Fast Fuzzy C-Means Clustering for Color Image Segmentation
IEEE transactions on fuzzy systems, 2019 A great number of improved fuzzy c-means (FCM) clustering algorithms have been widely used for grayscale and color image segmentation. However, most of them are time-consuming and unable to provide desired segmentation results for color images due to two
Tao Lei +5 more
semanticscholar +1 more source