Agent-Interacted Big Data-Driven Dynamic Cartoon Video Generator

Abstract

This study presents a novel method for animating videos using three Kaggle cartoon faces data sets. Dynamic interactions between cartoon agents and random backgrounds, as well as Gaussian blur, rotation, and noise addition, make cartoon visuals look better. This approach also evaluates video quality and animation design by calculating the backdrop colour's average and standard deviation, ensuring visually appealing material. This technology uses massive datasets to generate attractive animated videos for entertainment, teaching, and marketing.

Reason for Expression of Concern:

The Editors wish to alert readers to potential concerns regarding the reliability of the findings reported in “Agent-Interacted Big Data-Driven Dynamic Cartoon Video Generator”.  The journal has initiated an additional editorial assessment of the article’s methodology, data provenance, and reported outcomes to confirm their reliability and reproducibility.

This notice is issued to ensure transparency while the review is ongoing. The Expression of Concern does not constitute a final determination regarding the validity of the work. The journal will update readers once the assessment is completed and will take any necessary editorial action in accordance with the journal’s policies and COPE guidance.
See expression of concern available at:

https://doi.org/10.58496/MJCS/2026/001

https://mesopotamian.press/journals/index.php/bigdata/article/view/1048