Resources and End-to-End Neural Network Models for Arabic Image Captioning

Author:

ElJundi Obeida1,Dhaybi Mohamad1,Mokadam Kotaiba2,Hajj Hazem1,Asmar Daniel3

Affiliation:

1. American University of Beirut, Electrical and Computer Engineering Department, Lebanon, --- Select a Country ---

2. American University of Beirut, Civil and Environmental Engineering Department, Lebanon, --- Select a Country ---

3. American University of Beirut, Mechanical Engineering Department, Lebanon, --- Select a Country ---

Publisher

SCITEPRESS - Science and Technology Publications

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Taylor African vulture optimization algorithm with hybrid deep convolution neural network for image captioning system;Multimedia Tools and Applications;2024-01-23

2. Ar-CM-ViMETA: Arabic Image Captioning based on Concept Model and Vision-based Multi-Encoder Transformer Architecture;The International Arab Journal of Information Technology;2024

3. Enhancing Cross-Lingual Image Description: A Multimodal Approach for Semantic Relevance and Stylistic Alignment;Computers, Materials & Continua;2024

4. Utilizing Deep Learning Technique for Arabic Image Captioning;Lecture Notes on Data Engineering and Communications Technologies;2024

5. An overview of the Image Description Systems in Arabic Language;2023 20th ACS/IEEE International Conference on Computer Systems and Applications (AICCSA);2023-12-04

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