Improvement of Image Processing with Modern Tools

This research paper describes an implementation of an image labeling algorithm using Tensorflow, Keras, and Python, and an optimization proposal using image compression techniques. The goal is to use image compression techniques to minimize data size, execution time, and computing resources. Machine learning applications have many limitations in terms of power consumption, processing power, and dataset size that often reduce their real-time efficiency. Applied use case. By trying to mitigate such obstacles, we can find new ways to apply machine learning to simpler real-world applications