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Abstract: Grayscale image colorization is a challenging task in computer vision, with significant applications in various domains such as image restoration, enhancement, and historical image analysis. This research paper introduces an innovative approach to grayscale image colorization utilizing adaptive techniques. By leveraging a pre-trained deep learning model and incorporating adaptive colorization methods, our approach aims to enhance the quality and accuracy of colorization results. Experimental evaluation demonstrates the effectiveness of our method in producing vibrant and realistic colorized images, showcasing its potential for practical applications.