1 November 1992 Clustering of noisy image data using an adaptive neuro-fuzzy system
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Proceedings Volume 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods; (1992) https://doi.org/10.1117/12.131611
Event: Applications in Optical Science and Engineering, 1992, Boston, MA, United States
Abstract
Identification of outliers or noise in a real data set is often quite difficult. A recently developed adaptive fuzzy leader clustering (AFLC) algorithm has been modified to separate the outliers from real data sets while finding the clusters within the data sets. The capability of this modified AFLC algorithm to identify the outliers in a number of real data sets indicates the potential strength of this algorithm in correct classification of noise real data.
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Suryalakshmi Pemmaraju, Sunanda Mitra, "Clustering of noisy image data using an adaptive neuro-fuzzy system", Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131611; https://doi.org/10.1117/12.131611
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