Results 181 to 190 of about 7,930 (201)

Research in SVM Sample Optimizes of ISODATA Algorithm

Advanced Materials Research, 2012
Support Vector Machine is widely used in data classification, but in the case of more training samples, the training time is longer. To solve this problem, use the ISODATA clustering algorithm to cluster samples to obtain the new cluster center, together with high similarity to the error for the sample to form a new cluster of training samples ...
Zhen Jiang Zhao, Wei Gao, Huai Zhong Wang, Ke Fei Zhang   +3 more
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High quality voice conversion based on ISODATA clustering algorithm

2017 12th International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 2017
Two main challenges introduced in current voice conversion are the dependence on parallel training data and the trade-off between speaker similarity and speech quality. To tackle the latter problem, this paper proposes a novel conversion method based on Iterative Self-organizing DATA Analysis Techniques Algorithm (ISODATA) clustering algorithm ...
Yanping Li, Yutao Zuo, Zhen Yang, Xi Shao   +3 more
openaire   +1 more source

Automatic segmentation of pancreatic images using ISODATA alorithm

Journal of Clinical Oncology, 2006
14149 Background: Pancreatic cancer is the second most common gastrointestinal malignancy in the United States, where it ranks 4th among all deaths caused by cancers. Early detection of pancreatic cancer remains a challange. Methods: MR images with different T1 and T2 weighting from the anatomical regions with the same imaging parameters were ...
B. Biswal, N. Shah, N. Shah, M. Trivedi, S. Nayak, H. Dave   +5 more
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Clustering Analysis for fMRI Dataset based on ISODATA Algorithm

2005 International Conference on Neural Networks and Brain, 2006
In the paper, the modified fuzzy c-means (MFc) is firstly used to treat the ill-balanced fMRI dataset to improve the efficiency, remove the redundance and reduce the population of analyzed voxels. Then the iteration self-organization data analysis techniques algorithm (ISODATA) method, as the development of data-driving methods, is utilized to find out
null Xi Zheng, null Zhitong Cao, null Bo Shao, null Jiazhong Fang, null Guoguang He   +4 more
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On the Convergence of the Fuzzy Clustering Algorithm “Fuzzy ISODATA”

ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 1986
AbstractIn der vorliegenden Arbeit wird für den unscharfen Partitionierungsalgorithmus “Fuzzy ISODATA” gezeigt, daß ausgehend von beliebigem Startpunkt jeder Häufungspunkt der generierten Folge ein stationärer Punkt des erweiterten, Quadratischen‐Fehlersummen‐Funktionals ist, welches als Partitionierungskriterium dient.
von Trzebiatowski, G., Bank, B.
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Images thresholding using ISODATA technique with gamma distribution

Pattern Recognition and Image Analysis, 2010
Image segmentation is a fundamental step in many applications of image processing. Many image segmentation techniques exist based on different methods such as classification-based methods, edge-based methods, region-based methods, and hybrid methods.
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An efficient parallel ISODATA algorithm based on Kepler GPUs

2014 International Joint Conference on Neural Networks (IJCNN), 2014
ISODATA is a well-known clustering algorithm used in various areas. It employs a heuristic strategy allowing the clusters based on the nearest neighbor rule to split and merge as appropriate. However, since the volume of the data to be clustered in real world is growing continuously, the efficiency of serial ISODATA has become a serious practical issue.
Shiquan Yang, Jianqiang Dong, Bo Yuan
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An adaptive isodata fuzzy clustering algorithm with partial supervision

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012
Semi-supervised learning uses large amount of unlabeled data, combined with labeled data, to guide the learning process. This paper introduces a new clustering algorithm with partial supervision based on an adaptive distance. The proposed method furnishes a fuzzy partition and a prototype for each cluster by optimizing a criterion based on an adaptive ...
Valmir Macario, Francisco de A.T. de Carvalho   +1 more
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Curvelet Transform and ISODATA Thresholding for Retinal Vessel Extraction

2021
Researchers says eyes are good indicator of many diseases like Diabetic retinopathy, Glaucoma, Hyper tension, cardiac disease and many age related abnormalities. Here we aim to put forward a reliable, fast and computerized method to get the vessel network of fundus image, that can assist the ophthalmologist to diagnose the disease in early stage and ...
Sakambhari Mahapatra, U. R. Jena, Sonali Dash   +2 more
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Recovering valid clusters with ISODATA supervised by the CAIC

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 1988
The authors developed an unsupervised clustering method that is a variant of the well known ISODATA clustering algorithm. They replace the heuristic rules that control ISODATA with rules that search for the minimum value of an information theoretic criterion.
C.S. Carman, M.B. Merickel
openaire   +1 more source