Authors: Janković, Radmila 
Amelio, Alessia
Draganov, Ivo R.
Affiliations: Computer Science 
Mathematical Institute of the Serbian Academy of Sciences and Arts 
Title: Writer Identification from Historical Documents Using Ensemble Deep Learning Transfer Models
First page: 1
Last page: 5
Conference: 21st International Symposium INFOTEH-JAHORINA, INFOTEH 2022
Issue Date: 1-Jan-2022
Rank: M33
ISBN: 9781665437783
DOI: 10.1109/INFOTEH53737.2022.9751301
Abstract: 
Handwriting recognition is a challenging task and with the advancements in the development of the deep learning such task can be performed even for very limited documents. This paper aims to perform writer identification and retrieval from historical documents using an ensemble of convolutional neural network models that were built using the Inception-ResNet-v2 pre-trained architecture. The dataset comprises 170 images grouped in 34 classes. The results prove that the ensemble model outperforms single pre-trained models, obtaining an accuracy of 96%.
Keywords: cultural heritage | deep learning | ensemble learning | historical documents | writer identification
Publisher: IEEE

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