Image Colourization Using Autoencoder (Python code)
In this video, you will learn about image Colorization using Autoencoder. As, colorization of grayscale images is a time-consuming task traditionally done manually. However, machine learning techniques, particularly Convolutional Neural Networks (CNNs), offer a faster and more accurate solution. CNNs excel in identifying patterns in images, making them ideal for this task. Colorization has applications in various fields, including Cyber Forensics. CNNs have achieved remarkable success in image classification, with error rates below 4% in challenges like ImageNet. This project will employ Python and OpenCV for implementation. CNNs' ability to learn and perceive colors, patterns, and shapes makes them well-suited for colorization as these aspects are closely related to color decisions.
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