E. Diday, G. Govaert, Y. Lechevallier, and J. Sidi, "Clustering in pattern recognition," in Digital Image Processing, J.-C. Simon, R. Haralick, and eds, Eds: Kluwer edition, 1981, pp. 19-58.Diday, E., G. Govaert
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Clustering is a prominent, practical, and attractive research trend often applied in pattern recognition, image segmentation, information retrieval, and filtering [16,83]. Clusters can be formed from similar data in solving different problems [69]. In clustering [37], nodes are categorized into dis...
2023, Pattern Recognition Citation Excerpt : Clustering, aiming to discover the underlying cluster structure in objects [1,2], forms a significant area in unsupervised learning and plays an indispensable role in pattern recognition [3,4], data mining [5], machine learning [6] and so on. ...
pattern is assigned to one of the categories according to the decision rule. Since we are interested in the classes of documents that have been assigned by the user, we can use pattern recognition techniques to try to classify previously unseen documents into the user's categories. While ...
1. Pattern Discovery Clustering allows for the identification of inherent patterns and structures within datasets. By grouping similar data objects together, clustering helps in revealing natural clusters and associations that may not be apparent through simple observation. It enables the discovery of unde...
Geoscience Australia. Record 2007/10, 58pp. Jain, A. K. 2009. "Data Clustering: 50 years beyond K-Means." Pattern Recognition Letters. https://doi.org/10.1016/j.patrec.2009.09.011.In this topic Potential applications Inputs Clustering Method Outputs Best practices Additional Resources...
Ray S, Turi RH (1999) Determination of number of clusters in k-means clustering and application in colour image segmentation. In: Proceedings of the 4th international conference on advances in pattern recognition and digital techniques, Calcutta, India, pp 137–143 Rhodes JD, Cole WJ, Upshaw CR...
in nature, returning different structures for different runs of the algorithm. These different structures, even though they tend to be similar in quality based on the optimization criterion, can be rather different (see Goodet al.7for examples in the context of modularity maximization). Further...
Clustering is a fundamental task in pattern recognition and data mining, and better clustering results are beneficial for the development of downstream computer vision tasks, such as object detection (Li et al., 2023), object classification (Fulare et al., 2023) and others. Compared to the sing...