Enhancing Image SEO using Deep Learning Algorithms: A Research Approach - Amara, Marwa; Zaghdoud, Radhia; Rhaiem, Olfa Ben; Althubiti, Ebtihal (Engineering, Technology & Applied Science Research, 2024)
Visual content influences profoundly user interactions and search engine rankings. Traditional SEO techniques, while foundational, often fall short in the swiftly changing search landscape. This paper presents a cutting-edge solution that leverages the power of deep learning and generative AI to redefine image SEO. Through the innovative integration of the AWS Rekognition’s image analysis and ChatGPT’s advanced natural language processing, we automate and refine the creation of alt-texts, ensuring they are not only precise, but also SEO-enriched. The result is a harmonious blend of technology and strategy that significantly boosts online content discoverability. Using a specific website as a test environment, the proposed methodology demonstrated a profound impact on SEO performance. Initially, no images on the webpage had alt-texts. After applying the AI-driven approach, all images were equipped with descriptive, SEO-optimized alt attributes, markedly improving their visibility in search engine results. These results underscore the effectiveness of integrating advanced AI technologies in SEO strategies, providing a scalable and effective framework for enhancing digital content accessibility and search engine rankings.