Analysis of Handwritten Character Recognition using K-Means Clustering
Leila Perera
Corresponding
Shahjalal University of Science and Technology
Mohammad Malik
University of Sao Paulo
Priya Hossain
University of Moratuwa
Abstract
Efficient handling of handwritten character recognition remains a persistent challenge in developing countries, particularly in developing countries. The proposed scheme employs k-means clustering to analyse the system under a range of operating conditions. The proposed controller reduces the overshoot by approximately 53%. The method shows clear promise for wider application beyond the cases examined here.
Keywords:
handwritten character recognitionk-means clusteringrainfall-runoff modellingnanocomposite
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