Enhancing Clarity with Techniques for Recognizing Blurred Objects in Low Quality Images Using Python

Авторы

Ключевые слова:

Image processing, blurred objects, low-quality images, Python, deep learning, Machine learning, restoration, recognition

Аннотация

This article explores methods for enhancing and recognizing blurred objects in low-quality images using Python. We delve into image processing techniques, machine learning algorithms, and deep learning models to restore and identify obscured objects. By examining existing literature and employing various Python libraries, we demonstrate practical implementations and their effectiveness. This study aims to provide a comprehensive guide for researchers and developers working with degraded visual data, presenting both theoretical insights and practical applications.

Биография автора

Soliev Bakhromjon

Главный редактор журнала

Библиографические ссылки

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Загрузки

Опубликован

2024-06-05

Как цитировать

Bakhromjon, S., Zulunov, R., & Ermatova, Z. (2024). Enhancing Clarity with Techniques for Recognizing Blurred Objects in Low Quality Images Using Python . Потомки Аль-Фаргани, 1(2), 336–340. извлечено от https://al-fargoniy.uz/index.php/journal/article/view/439

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