Fuzzy C-means (FCM) clustering algorithm: a decade review from 2000 to 2014
The Fuzzy c-means is one of the most popular ongoing area of research among all types of
researchers including Computer science, Mathematics and other areas of engineering, as …
researchers including Computer science, Mathematics and other areas of engineering, as …
Matchmaking in reward-based crowdfunding platforms: A hybrid machine learning approach
S Qu, L Xu, SK Mangla, FTS Chan, J Zhu… - International Journal of …, 2022 - Taylor & Francis
Traditional clustering methods fail to accurately cluster the feature vectors of backers and
macth the potential backers to compatible crowdfunding projects, mainly due to their …
macth the potential backers to compatible crowdfunding projects, mainly due to their …
Machine learning techniques in clinical vision sciences
This review presents and discusses the contribution of machine learning techniques for
diagnosis and disease monitoring in the context of clinical vision science. Many ocular …
diagnosis and disease monitoring in the context of clinical vision science. Many ocular …
Fuzzy c-means clustering with local information and kernel metric for image segmentation
In this paper, we present an improved fuzzy C-means (FCM) algorithm for image
segmentation by introducing a tradeoff weighted fuzzy factor and a kernel metric. The …
segmentation by introducing a tradeoff weighted fuzzy factor and a kernel metric. The …
A messy state of the union: Taming the composite state machines of TLS
The Transport Layer Security (TLS) protocol supports various authentication modes, key
exchange methods, and protocol extensions. Confusingly, each combination may prescribe …
exchange methods, and protocol extensions. Confusingly, each combination may prescribe …
A robust fuzzy local information C-means clustering algorithm
This paper presents a variation of fuzzy c-means (FCM) algorithm that provides image
clustering. The proposed algorithm incorporates the local spatial information and gray level …
clustering. The proposed algorithm incorporates the local spatial information and gray level …
[書籍][B] Modern algorithms of cluster analysis
ST Wierzchoń, MA Kłopotek - 2018 - Springer
This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …
interested in cluster analysis, lists major application areas, basic theoretical and practical …
Robust image segmentation using FCM with spatial constraints based on new kernel-induced distance measure
Fuzzy c-means clustering (FCM) with spatial constraints (FCM/spl I. bar/S) is an effective
algorithm suitable for image segmentation. Its effectiveness contributes not only to the …
algorithm suitable for image segmentation. Its effectiveness contributes not only to the …
Fast and robust fuzzy c-means clustering algorithms incorporating local information for image segmentation
Fuzzy c-means (FCM) algorithms with spatial constraints (FCM_S) have been proven
effective for image segmentation. However, they still have the following disadvantages:(1) …
effective for image segmentation. However, they still have the following disadvantages:(1) …
Prediction interval estimation of aeroengine remaining useful life based on bidirectional long short-term memory network
Reliable and accurate aeroengine remaining useful life (RUL) prediction plays a key role in
the aeroengine prognostics and health management (PHM) system. However, due to the …
the aeroengine prognostics and health management (PHM) system. However, due to the …