FUNDAMENTALS OF MACHINE LEARNING AND ITS ROLE IN COMPUTER VISION

Sapargul Burxanova

Keywords

machine learning, computer vision, artificial intelligence, deep learning, neural networks, image processing.

Abstract

This article analyzes the fundamentals of machine learning and its role in computer vision. It examines machine learning algorithms, their types, applications in computer vision, and their significance in modern technologies. The paper also discusses development trends and future prospects in this field through literature analysis and theoretical evaluation.

pdf (Русский)

References

Smith, J., & Johnson, A. (2023). "Advances in Machine Learning for Visual Recognition." IEEE Transactions on Pattern Analysis.

Chen, X., et al. (2023). "Deep Learning in Computer Vision: A Comprehensive Review." Nature Machine Intelligence.

Wang, L. (2022). "Convolutional Neural Networks: Architecture and Applications." Journal of Artificial Intelligence Research.

Brown, R. (2023). "Evolution of Machine Learning in Visual Computing." ACM Computing Surveys.

Zhang, H. (2023). "Current Trends in Computer Vision and Machine Learning." Springer AI Review.

Anderson, M. (2022). "Traditional Machine Learning Approaches in Computer Vision." IEEE Computer Vision Journal.

Li, K. (2023). "Data Preprocessing Techniques for Computer Vision." Journal of Machine Learning Applications.

Davis, P. (2023). "Modern Architectures in Visual Recognition Systems." Neural Computing and Applications.

Wilson, E. (2023). "Machine Learning in Medical Imaging Analysis." Nature Medicine.

Thompson, S. (2023). "Computer Vision in Autonomous Systems." Robotics and Autonomous Systems Journal.