Enhancing Fashion Intelligence for Exceptional Customer Experience

The evolution of e-commerce has significantly transformed retail, with global sales expected to reach $6.4 trillion by 2024. The fashion industry, benefiting from technological advancements like artificial intelligence (AI), uses AI for product recommendations, inventory management, and personalized customer experiences. Despite these advances, challenges persist in image classification, sentiment analysis, personalized recommendations, and trend prediction. This research develops a comprehensive fashion intelligence system to enhance customer experiences. The system integrates multi-modal data fusion to combine predictions from various models, offering a holistic and accurate forecast of fashion trends. It employs explainable AI (XAI) for better sentiment analysis interpretability and a hybrid recommendation system that combines fashion styles and personality traits for more accurate suggestions. Adversarial learning techniques are used to enhance the robustness and security of image classifiers. Addressing these challenges, the system aims to significantly improve the online shopping experience for consumers and sellers by providing personalized, accurate, and trend-aware fashion recommendations.