A Comprehensive Multimodal Framework for Robust Forgery Detection in Social Media Images via Adaptive Gated Fusion of Convolutional Neural Networks, Vision Transformers, and Graph Neural Network Representations
- DOI
- 10.21203/rs.3.rs-10101431/v1
- Published
- 2026-07-23
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- Open access
- no
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BibTeX
@article{allodium:10.21203/rs.3.rs-10101431/v1,
title = {A Comprehensive Multimodal Framework for Robust Forgery Detection in Social Media Images via Adaptive Gated Fusion of Convolutional Neural Networks, Vision Transformers, and Graph Neural Network Representations},
author = {Alkishri W and Kamal S and Yousif J and Al-Bahri M.},
year = {2026},
doi = {10.21203/rs.3.rs-10101431/v1},
url = {https://doi.org/10.21203/rs.3.rs-10101431/v1}
}RIS
TY - JOUR TI - A Comprehensive Multimodal Framework for Robust Forgery Detection in Social Media Images via Adaptive Gated Fusion of Convolutional Neural Networks, Vision Transformers, and Graph Neural Network Representations AU - Alkishri W AU - Kamal S AU - Yousif J AU - Al-Bahri M. PY - 2026 DO - 10.21203/rs.3.rs-10101431/v1 UR - https://doi.org/10.21203/rs.3.rs-10101431/v1 ER -
APA
W, A., S, K., J, Y., & M., A. (2026). A Comprehensive Multimodal Framework for Robust Forgery Detection in Social Media Images via Adaptive Gated Fusion of Convolutional Neural Networks, Vision Transformers, and Graph Neural Network Representations. https://doi.org/10.21203/rs.3.rs-10101431/v1
Source records
- europe-pmc · retrieved 2026-09-25T13:55:21.287Z