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RETRACTION

Retraction: A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique

Computers, Materials & Continua Editorial Office

Computers, Materials & Continua 2026, 88(1), 85 https://doi.org/10.32604/cmc.2026.083414

This article is a retraction of:

A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique
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Abstract

This article has no abstract.

The published article titled “A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique” has been retracted from Computers, Materials & Continua, Vol. 85, No. 3, 2025, pp. 5671–5702.

DOI: 10.32604/cmc.2025.070422

URL: https://www.techscience.com/cmc/v85n3/64202

Following an investigation, the article was found to contain significant overlap with previously published material, which violates the journal’s publication ethics policies and the guidelines of the Committee on Publication Ethics (COPE).

This retraction was approved by the Editor-in-Chief of the journal Computers, Materials & Continua.

The authors were informed of the retraction decision; however, they have not provided any response regarding the retraction.


Cite This Article

APA Style
Computers, , Office, M.&.C.E. (2026). Retraction: A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique. Computers, Materials & Continua, 88(1), 85. https://doi.org/10.32604/cmc.2026.083414
Vancouver Style
Computers , Office M&CE. Retraction: A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique. Comput Mater Contin. 2026;88(1):85. https://doi.org/10.32604/cmc.2026.083414
IEEE Style
Computers and M.&.C.E. Office, “Retraction: A Lightweight Multimodal Deep Fusion Network for Face Antis Poofing with Cross-Axial Attention and Deep Reinforcement Learning Technique,” Comput. Mater. Contin., vol. 88, no. 1, pp. 85, 2026. https://doi.org/10.32604/cmc.2026.083414


cc Copyright © 2026 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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