DIGITAL EYES: HOW OPTICS AND MATHEMATICS TEACH ARTIFICIAL INTELLIGENCE TO SEE

Authors

  • Khusiddinov Fakhriddin Shamsiddinovich Author

Keywords:

Keywords: artificial intelligence, optical systems, mathematical modeling, vision technologies

Abstract

Abstract: This article provides a comprehensive analysis of the concept of digital eyes, focusing on the role of optics and mathematical modeling in teaching artificial intelligence to see. Based on historical and modern theories, global and regional research, and practical applications, it highlights the formation, developmental stages, and current challenges of artificial vision systems. Special attention is given to theoretical and practical approaches, critical analysis, and prospects, offering a holistic overview of scientific, programmatic, and technological advancements in the field of digital eyes.

References

1. Ballard, D. H., & Brown, C. M. (1982). Computer Vision. Prentice Hall.

2. Minsky, M., & Papert, S. (1969). Perceptrons: An Introduction to Computational Geometry. MIT Press.

3. LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.

4. Jo‘raev, A.H. (2018). Optik signallarni raqamli qayta ishlash: nazariy va amaliy asoslar. Toshkent: Fan.

5. Litjens, G., Kooi, T., Bejnordi, B. E., et al. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60–88.

6. Dosovitskiy, A., Beyer, L., Kolesnikov, A., et al. (2021). An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale. ICLR.

Published

2026-05-10

How to Cite

Khusiddinov Fakhriddin Shamsiddinovich. (2026). DIGITAL EYES: HOW OPTICS AND MATHEMATICS TEACH ARTIFICIAL INTELLIGENCE TO SEE. JOURNAL OF NEW CENTURY INNOVATIONS, 100(3), 14-18. https://journalss.org/index.php/new/article/view/29189