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Computer Science

Convolutional Neural Network Architecture for Offline Handwritten Characters Recognition

S. Hamida, B. Cherradi, H. Ouajji, A. Raihani

2019.11.21Learning and Analytics in Intelligent Systems

DOI: 10.1007/978-3-030-36778-7_41

tlooto Summary

The results obtained using different similarity measures such as accuracy, sensitivity and specificity confirm that the classification obtained by the proposed CNN architecture is the most accurate compared to the KNN studied in this work.

Abstract

Abstract is not available.

Citation format

HAMIDA, S., et al. Convolutional neural network architecture for offline handwritten characters recognition. Learning and Analytics in Intelligent Systems, 2019.