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A neural network framework for selecting real-time video enhancement algorithms on mobile devices.

Mudassir Khan1, Mohammed Inamur Rahman2, Riaz Ahmad Ziar3

  • 1Department of Computer Science, College of Computer Science, Applied College Tanumah, King Khalid University, Abha, Saudi Arabia.

Scientific Reports
|January 14, 2026
PubMed
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Selecting the best real-time video enhancement for mobile devices is challenging. A new fuzzy neural network model identifies Deep Learning Super Resolution as the optimal algorithm, improving performance and accuracy.

Area of Science:

  • Computer Vision
  • Artificial Intelligence
  • Signal Processing

Background:

  • Real-time video enhancement is vital for mobile applications like video calling and augmented reality.
  • Constraints in processing power, battery, and memory complicate algorithm selection.
  • Existing methods struggle to balance speed, quality, and complexity.

Purpose of the Study:

  • To develop a robust decision-making model for selecting real-time video enhancement algorithms.
  • To overcome the limitations of classical models in optimal algorithm selection.
  • To identify the most effective algorithm for mobile video enhancement.

Main Methods:

  • A novel decision-making model utilizing fuzzy neural networks with Sugeno-Weber norms was developed.
  • The model evaluates and selects appropriate video enhancement techniques.
Keywords:
Decision modelFuzzy neural networkReal-time video enhancement algorithms

Related Experiment Videos

  • Performance was validated against established decision-making methodologies.

    • Main Results:

    • The proposed fuzzy neural network model successfully identified an optimal algorithm.
    • Deep Learning Super Resolution was determined to be the most suitable real-time enhancement technique.
    • Verification confirmed the accuracy and reliability of the model's decisions.

    Conclusions:

    • The fuzzy neural network model offers a superior approach to selecting real-time video enhancement algorithms.
    • Deep Learning Super Resolution is recommended for optimal performance on mobile devices.
    • This research addresses a critical challenge in mobile multimedia processing.