Results 51 to 60 of about 2,884,172 (338)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 In the process of land cover segmentation from remote sensing image, there are some uncertainties such as “significant difference in class density”, “different objects with same spectrum”, and “same object with ...
Chengmao Wu, Xiaokang Guo
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Image segmentation using fuzzy clustering incorporating spatial information [PDF]
, 2004 Effective image segmentation cannot be achieved for a fuzzy clustering algorithm based on using only pixel intensity, pixel locations or a combination of the two.
Ali, Ameer +2 more
core
Cluster validity for fuzzy criterion clustering
1995 IEEE International Conference on Systems, Man and Cybernetics. Intelligent Systems for the 21st Century, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Esogbue, A.O., Liu, Baoding
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Three‐dimensional Antimony Sulfide Based Flat Optics
Advanced Functional Materials, EarlyView.This work presents the development of a grayscale electron beam lithography (g‐EBL) method for fabricating antimony trisulfide (Sb2S3) nanostructures with customizable 3D profiles. The refractive index of g‐EBL patterned Sb2S3 is determined based on the synergy of genetic algorithm and transfer matrix method.
Wei Wang +18 more
wiley +1 more source
Fuzzy Relational Fixed Point Clustering [PDF]
International Journal of Computational Intelligence Systems, 2009 The proposed relational fuzzy clustering method, called FRFP ( fuzzy relational fixed point), is based on determining a fixed point of a function of the desired membership matrix. The ethod is compared to other relational clustering methods.
Roelof K. Brouwer
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RESAMPLING FOR FUZZY CLUSTERING [PDF]
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 2007 Resampling methods are among the best approaches to determine the number of clusters in prototype-based clustering. The core idea is that with the right choice for the number of clusters basically the same cluster structures should be obtained from subsamples of the given data set, while a wrong choice should produce considerably varying cluster ...
openaire +2 more sources
Fuzzy Density Peaks Clustering
IEEE transactions on fuzzy systems, 2021 As an exemplar-based clustering method, the well-known density peaks clustering (DPC) heavily depends on the computation of kernel-based density peaks, which incurs two issues: first, whether kernel-based density can facilitate a large variety of data ...
Zekang Bian, F. Chung, Shitong Wang
semanticscholar +1 more source
Imaging of Biphoton States: Fundamentals and Applications
Advanced Functional Materials, EarlyView.Quantum states of two photons exhibit a rich polarization and spatial structure, which provides a fundamental resource of strongly correlated and entangled states. This review analyzes the physics of these intriguing properties and explores the various techniques and technologies available to measure them, including the state of the art of their ...
Alessio D'Errico, Ebrahim Karimi
wiley +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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Fuzzy determination of informative frequency band for bearing fault detection [PDF]
, 2016 Detecting early faults in rolling element bearings is a crucial measure for the health maintenance of rotating machinery. As faulty features of bearings are usually demodulated into a high-frequency band, determining the informative frequency band (IFB ...
Abonyi +28 more
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