Results 31 to 40 of about 606,186 (241)
MMKK++ algorithm for clustering heterogeneous images into an unknown number of clusters
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2018 In this paper we present a suggested automatic clustering procedure with the main aim to predict the number of clusters of unknown, heterogeneous images.
Dávid Papp, Gábor Szűcs
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Efficient similarity-based data clustering by optimal object to cluster reallocation. [PDF]
PLoS ONE, 2018 We present an iterative flat hard clustering algorithm designed to operate on arbitrary similarity matrices, with the only constraint that these matrices be symmetrical.
Mathias Rossignol +2 more
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BarekengPopulation data is an important piece of information that is useful for regional planning and development. Insight into the state of an area is more straightforward to observe if there are grouped sub-districts.
Denny Nurdiansyah +4 more
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Distributed Kernel K-Means for Large Scale Clustering
, 2017 Clustering samples according to an effective metric and/or vector space representation is a challenging unsupervised learning task with a wide spectrum of applications.
Decherchi, Sergio +2 more
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Schwartz kernel theorem for the Fourier hyperfunctions [PDF]
, 1995 The purpose of this paper is to give a direct proof of the Schwartz kernel theorem for the Fourier hyoerfunctions. The Schwartz kernel theorem for the Fourier hyperfunctions means that with every Fourier hyperfunction K in ..
Chung Soon-Yeon, Kim Dohan, Lee Eun Gu
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Weighted Mutual Information for Aggregated Kernel Clustering
Entropy, 2020 Background: A common task in machine learning is clustering data into different groups based on similarities. Clustering methods can be divided in two groups: linear and nonlinear. A commonly used linear clustering method is K-means.
Nezamoddin N. Kachouie, Meshal Shutaywi
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Twin Learning for Similarity and Clustering: A Unified Kernel Approach
, 2017 Many similarity-based clustering methods work in two separate steps including similarity matrix computation and subsequent spectral clustering. However, similarity measurement is challenging because it is usually impacted by many factors, e.g., the ...
Cheng, Qiang, Kang, Zhao, Peng, Chong
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Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
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SN Applied Sciences, 2021 Customer churn has been considered as one of the key issues in the operations of the corporate business sector, as it influences the turnover directly.
C. K. Praseeda, B. L. Shivakumar
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