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The research highlights the rapid development and increasing adoption of artificial intelligence (AI) technologies into our daily lives, particularly through applications and gadgets such as voice assistants, weather forecasts and advanced photo processing capabilities.This integration of neural networks into everyday tasks demonstrates how artificial intelligence can significantly improve the quality of photo processing, solving the problems of damage, color distortion and other defects.The main goal of this article is to explore the techniques that neural networks offer for restoring, editing and saving important images, as well as to consider the possibilities of their improvement and adaptation to people's needs.Analyzes how the AI image processing process includes several key steps, from image acquisition to image enhancement and restoration.Computer vision plays a critical role in this process, providing tools to optimize images for machine learning.Various methods of processing, compression and expansion of photographic data are considered, which contribute to increasing the efficiency of AI models in the processing of photographic materials.The problem of retraining models and methods for solving it are separately covered, including model simplification, early stopping, data augmentation, regularization, and the dropout method.Such strategies improve the generalizability of the model, providing qualitative results.The findings highlight that artificial intelligence and machine learning are opening up new horizons in image processing, providing tools for face recognition, object detection, and text recognition, as well as contributing to the development of deep learning.It is important to choose the appropriate tools and techniques to achieve optimal results, considering the potential of artificial intelligence and its impact on the future of photo processing.
Ruslana Buryk (Tue,) studied this question.