Special Issues
Table of Content

Advances in AI-Driven Computational Modeling for Image Processing

Submission Deadline: 30 April 2025 View: 176 Submit to Special Issue

Guest Editors

Dr. Sathishkumar V E

Email: sathishv@sunway.edu.my

Affiliation: Department of Computing and Information Systems, Sunway University, Malaysia

Homepage:

Research Interests: Data Mining, Machine Learning, Quantum Computing

图片3.png


Dr. R. Karthik

Email: r.karthik@vit.ac.in

Affiliation: Centre for Cyber Physical Systems, Vellore Institute of Technology, India

Homepage:

Research Interests: Medical image processing, Computer Vision, Healthcare

图片4.png


Summary

The special issue on "Advances in AI-Driven Computational Modeling for Image Processing" aims to provide a comprehensive platform for researchers and practitioners to discuss the latest advancements, challenges, and future directions in the integration of artificial intelligence (AI) with computational modeling techniques for image processing applications. This special issue seeks to highlight innovative approaches and methodologies that leverage AI to enhance image processing tasks such as image recognition, segmentation, restoration, enhancement, and understanding.


The objectives of this special issue are to:

1. Present state-of-the-art research on AI-driven computational modeling techniques for image processing.

2. Explore novel algorithms and frameworks that integrate AI with image processing applications.

3. Discuss real-world applications and case studies demonstrating the effectiveness of AI in image processing.

4. Identify current challenges and future research directions in the field.


We invite original research papers, review articles, and case studies on topics including, but not limited to:

· Deep learning architectures for image processing

· AI-driven image segmentation and object detection

· Image enhancement and restoration using AI techniques

· Computational modeling for medical image analysis

· AI-based image synthesis and generation

· Real-time image processing using AI

· AI in remote sensing and satellite image processing

· AI-driven techniques for image compression and coding

· Explainable AI in image processing

· Benchmarking and evaluation of AI models for image processing

· Ethical and societal implications of AI in image processing



Published Papers


  • Open Access

    ARTICLE

    An Enhanced Lung Cancer Detection Approach Using Dual-Model Deep Learning Technique

    Sumaia Mohamed Elhassan, Saad Mohamed Darwish, Saleh Mesbah Elkaffas
    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.1, pp. 835-867, 2025, DOI:10.32604/cmes.2024.058770
    (This article belongs to the Special Issue: Advances in AI-Driven Computational Modeling for Image Processing)
    Abstract Lung cancer continues to be a leading cause of cancer-related deaths worldwide, emphasizing the critical need for improved diagnostic techniques. Early detection of lung tumors significantly increases the chances of successful treatment and survival. However, current diagnostic methods often fail to detect tumors at an early stage or to accurately pinpoint their location within the lung tissue. Single-model deep learning technologies for lung cancer detection, while beneficial, cannot capture the full range of features present in medical imaging data, leading to incomplete or inaccurate detection. Furthermore, it may not be robust enough to handle the… More >

Share Link