Results 251 to 260 of about 617,742 (295)

Spatial Models for Fuzzy Clustering

Computer Vision and Image Understanding, 2001
Summary: A novel approach to fuzzy clustering for image segmentation is described. The fuzzy \(C\)-means objective function is generalized to include a spatial penalty an the membership functions. The penalty term leads to an iterative algorithm that is only slightly different from the original fuzzy \(C\)-means algorithm and allows the estimation of ...
openaire   +2 more sources

Spatial Multidimensional Sequence Clustering

Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
Measurements at different time points and positions in large temporal or spatial databases requires effective and efficient data mining techniques. For several parallel measurements, finding clusters of arbitrary length and number of attributes, poses additional challenges.
Ira Assent, Ralph Krieger, Boris Glavic, Thomas Seidl   +3 more
openaire   +1 more source

Obstacle constraint spatial clustering

SPIE Proceedings, 2009
Constraints in the real world must be seriously considered in the process of spatial clustering. In this paper we study the spatial clustering issue in the presence of obstacles. The cluster algorithm is based on the K-medoid algorithm, and an improved algorithm Guo Tao is introduced to obtain the distance of spatial objects in the presence of ...
Yuan-ni Wang, Fu-ling Bian
openaire   +1 more source

Random spatial subspace clustering

Knowledge-Based Systems, 2015
Strong spatial or time correlation exists in many types of data, for example, the hyperspectral data acquired by a spectrometer scanning through rock samples from a drill hole. It is of practical interests to identify spatially continuous segments in a given data set where we know a priori that the samples are strongly correlated spatially. Recently, a
Guo, Yi (R18457), Gao, Junbin, Li, Feng
openaire   +2 more sources

SPATIAL CLUSTERING OF ARTISTS [PDF]

, 2013
Surveys of artists’ location choices show that they disproportionately reside in large cities. This paper introduces a model that attempts to explain this urban preference. The model includes four factors: access to other artists, access to consumers, access to service jobs, and housing affordability.
Andersson , Åke E., Andersson , David E., Daghbashyan, Zara, Hårsman, Björn   +3 more
openaire  

Integrative oncology: Addressing the global challenges of cancer prevention and treatment

Ca-A Cancer Journal for Clinicians, 2022
Jun J Mao,, Msce, Lorenzo Cohen, Karen M Mustian   +2 more
exaly  

Spatially-Encouraged Spectral Clustering

2018
Spatially-constrained clustering is a central concern in geographic data science. It finds applications in epidemiology, sociological neighborhood study, criminology, operations research, statistics, and econometrics, to name a few. One recently-developed method provides a powerful technique that ostensibly allows contiguity and attribute similarity to
openaire   +1 more source

Spatially Agglomerative Clustering

2008
Shashi Shekhar, Hui Xiong
openaire   +1 more source

Clustered Distributed Spatial Multiplexing

MILCOM 2022 - 2022 IEEE Military Communications Conference (MILCOM), 2022
Andreas Polydoros, Cenk Kose
openaire   +1 more source

Spatial Cluster Modeling

Journal of the American Statistical Association, 2004
openaire   +1 more source