Briber, AminaChibani, Youcef2022-04-142022-04-142022-01-24Briber, Amina. Chibani,Youcef. On the use of the convolutional autoencoder for Arabic writer identification using handwritten text fragments. Forum of Artificial Intelligence and Its Applications. 24-26 Jan 2022. Faculty of Exat science. University of Eloued. [visited in ../../….]. available from [copy the link here]https://dspace.univ-eloued.dz/handle/123456789/10827Forum Intervention of Artificial Intelligence and Its Applications. Faculty of Exat science. University of ElouedConvolutional autoencoders (CAE) are designed to reconstruct the input image to the output in a near-perfect way via a compact data namely encoded data containing relevant features. The encoded data can be used in various applications as for compressing or classifying the image. The present paper tries to investigate the use of the CAE for writer identification using handwritten text fragments. Hence, the CAE is used for generating features, which is fed to the distance-based classifier. Experimental evaluation is performed on the wellknown IFN/ENIT dataset containing 411 writers. During training, a subset is selected from the 411 writers containing only 11 writers allowing to produce a lite CAE. Experimental results show an identification rate of 92.70% using the whole dataset when the feature vector is appropriately normalized.enWriter identification, Handwritten, Text fragment, Convolutional autoencoders.Other