A performance analysis of transformer-based deep learning models for Arabic image captioning
Image captioning has become a fundamental operation that allows the automatic generation of text descriptions of images. However, most existing work focused on performing the image captioning task in English, and only a few proposals exist that address the image captioning task in Arabic. This paper...
Main Authors: | Ashwaq Alsayed, Thamir M. Qadah, Muhammad Arif |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-10-01
|
Series: | Journal of King Saud University: Computer and Information Sciences |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S131915782300304X |
Similar Items
-
A Systematic Literature Review on Using the Encoder-Decoder Models for Image Captioning in English and Arabic Languages
by: Ashwaq Alsayed, et al.
Published: (2023-09-01) -
An Attentive Fourier-Augmented Image-Captioning Transformer
by: Raymond Ian Osolo, et al.
Published: (2021-09-01) -
Arabic Captioning for Images of Clothing Using Deep Learning
by: Rasha Saleh Al-Malki, et al.
Published: (2023-04-01) -
Cross Encoder-Decoder Transformer with Global-Local Visual Extractor for Medical Image Captioning
by: Hojun Lee, et al.
Published: (2022-02-01) -
An Analysis of the Use of Feed-Forward Sub-Modules for Transformer-Based Image Captioning Tasks
by: Raymond Ian Osolo, et al.
Published: (2021-12-01)