Proceedings of the First International Conference on Artificial Intelligence, Smart Technologies and Communications (AISTC 2025)

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Symbiotic AI Systems for Enhanced Image Classification

Authors
Slim Rouabah1, *, Youcef Naas1
1Department of Electronics and Communication, Djilali Bounaama University of Khemis Miliana, N14, Khemis Miliana, 44001, Ain Defla, Algeria
*Corresponding author. Email: s.rouabah@univ-dbkm.dz
Corresponding Author
Slim Rouabah
Available Online 5 August 2025.
DOI
10.2991/978-94-6463-805-9_3How to use a DOI?
Keywords
Symbiotic AI; Convolutional Neural Network; classification
Abstract

This paper introduces Symbiotic AI (SAI), an architecture based on machine learning framework that mimics self-improvement mechanisms of a real brain. It incorporates an Automated Feedback Loop (AFL) that retrains the model on misclassified data, enhancing adaptability and classification. This framework is tested and evaluated on real and fake MNIST datasets and medical chest Xrays images utilizing metrics such as accuracy, loss, F1-score and the processing time. One of the purposes of this work is to highlight the benefits of integrating an AFL into neural network training, demonstrating self-improvement and adaptability of the model. Overall, this novel technique promises a robust framework for advancing image classification systems. This work contributes to the ongoing development of AI systems capable of addressing real-world challenges in computer vision, highlighting the trade-offs between iteration count and architecture complexity, to prevent overfitting and to optimize performance. Our research will extend the exploitation of the symbiotic AI to other image datasets and real-time applications, fostering more intelligent and adaptive AI solutions for complex computer vision challenges.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the First International Conference on Artificial Intelligence, Smart Technologies and Communications (AISTC 2025)
Series
Advances in Intelligent Systems Research
Publication Date
5 August 2025
ISBN
978-94-6463-805-9
ISSN
1951-6851
DOI
10.2991/978-94-6463-805-9_3How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Slim Rouabah
AU  - Youcef Naas
PY  - 2025
DA  - 2025/08/05
TI  - Symbiotic AI Systems for Enhanced Image Classification
BT  - Proceedings of the First International Conference on Artificial Intelligence, Smart Technologies and Communications (AISTC 2025)
PB  - Atlantis Press
SP  - 12
EP  - 20
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-805-9_3
DO  - 10.2991/978-94-6463-805-9_3
ID  - Rouabah2025
ER  -