@inproceedings{d9cfac77d06342bb8d7223552a095d51,
title = "Author Identification from Handwritten Characters using Siamese CNN",
abstract = "The NIST Special Database 19 has been studied to solve character recognition tasks. We present a different study on this dataset, where we do author identification using features learned from handwritten characters. Recent studies in computer vision demonstrate that Siamese Convolutional Networks enjoyed successes in image information retrieval tasks. This technique has previously been applied in the identification of people using face image data producing start-of-the-art performance. We apply Siamese convolutional neural networks in author verification based on the handwritten characters. Employing a pairwise-loss approach, we developed a three-layer Convolutional Neural Network, with three fully connected layers, we achieved verification accuracy of 80% on average with unseen test data.",
keywords = "Author verification, Convolutional Neural Networks, distance metric, Neural Network, Siamese",
author = "Nkosikhona Dlamini and {Van Zyl}, {Terence L.}",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019 ; Conference date: 21-11-2019 Through 22-11-2019",
year = "2019",
month = nov,
doi = "10.1109/IMITEC45504.2019.9015897",
language = "English",
series = "Proceedings - 2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings - 2019 International Multidisciplinary Information Technology and Engineering Conference, IMITEC 2019",
address = "United States",
}