Abstract

Abstract -This project aims to explore the application of deep learning techniques in image colorization using artificial intelligence (AI). Leveraging convolutional neural networks (CNNs) and generative adversarial networks (GANs), our objective is to develop a robust system capable of accurately and efficiently adding color to grayscale images. By training the model on a diverse dataset of grayscale images paired with their corresponding color versions, we aim to create a colorization tool that can replicate human-like color choices and produce visually appealing results. The proposed methodology involves preprocessing the dataset, designing and training the deep learning model, and evaluating its performance on test datasets. The anticipated outcome is a user-friendly image colorization tool that can be integrated into various applications, enhancing the visual experience and productivity of users. keywords: Deep Learning, Image Colorization, Convolutional Neural Networks (CNNs), Generative Adversarial Networks (GANs), Artificial Intelligence (AI), Grayscale Images..

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