Submissions

Author Guidelines

Authors are invited to make a submission to this journal. All submissions will be assessed by an editor to determine whether they meet the aims and scope of this journal. Those considered to be a good fit will be sent for peer review before determining whether they will be accepted or rejected.

Before making a submission, authors are responsible for obtaining permission to publish any material included with the submission, such as photos, documents and datasets. All authors identified on the submission must consent to be identified as an author. Where appropriate, research should be approved by an appropriate ethics committee in accordance with the legal requirements of the study's country.

An editor may desk reject a submission if it does not meet minimum standards of quality. Before submitting, please ensure that the study design and research argument are structured and articulated properly. The title should be concise and the abstract should be able to stand on its own. This will increase the likelihood of reviewers agreeing to review the paper. When you're satisfied that your submission meets this standard, please follow the checklist below to prepare your submission.

Submission Preparation Checklist

All submissions must meet the following requirements.

This submission meets the requirements outlined in the Author Guidelines.
This submission has not been previously published, nor is it before another journal for consideration.
All references have been checked for accuracy and completeness.
All tables and figures have been numbered and labeled.
Permission has been obtained to publish all photos, datasets and other material provided with this submission.

Topic: Machine Learning Based Techniques for Image and Video Processing

Machine learning-based techniques have been widely used in various computer vision, automation, image and video processing applications, leading to leapfrogging improvements in performance. We would like to gather researchers here to demonstrate the latest research and approaches regarding various aspects of image and video processing in the era of Big Data.

This topic invites researchers to contribute original research articles that stimulate the continuing efforts to understand image and video processing algorithms, data structures, optimization trade-offs, architectures, and their applications.

Topic: Deepfake Detection and Image Processing

Deepfake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image. The goal of Deepfake Detection and Image Processing is to identify such manipulations and distinguish them from real videos or images.

We welcome manuscripts on all aspects of the Deepfake creation and detection domain, including image processing, adversarial forensics, and generative models on images and video. Topics of interest include, but are not limited to:

Source image reconstruction from Deepfakes

Generative model recognition
Adversarial forensics on deepfake content
Generative models for deepfake creation
Image/video forgery creation and detection
Facial manipulation and synthesis techniques
Image/video Deepfake detection
Identification and localization of the manipulated Region of Interest (ROI)
Detection of structural/textural changes in an image due to forgery or manipulation
Detection of post processing effects from Deepfake generation
Multiscale and multimodal transformers for Deepfake detection
Visual cryptography and watermarking techniques for authentication and forgery detection
Attention and capsule networks for Deepfake detection
Morphing and Deepfake Attacks on facial recognition systems

Selected Papers from Conferences

This section will publish selected papers from conference.

Special Issue: Advancements in AI-Driven Image Processing and Graphics: Techniques, Applications, and Challenges

Submission Deadline: December 25, 2025

Special Issue Editors

Guest Editor
Prof. Yousef Farhaoui, Moulay Ismail University, Morocco
Research areas: Computer Science, AI, Image Processing, Big Data

Prof. Hamed Taherdoost, Chair of RSAC at University Canada West, Canada
Research areas: Computer Science, C.Cyber

Prof. Mohamed Fnadi, University of the Littoral Côte d'Opale, France
Research areas: Computer Science

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