Smart Retail Experience based on Augmented Reality using Deep Learning and Computer Vision

Augmented Reality (AR), combined with Deep Learning and Computer Vision, is revolutionizing the retail sector by enhancing customer engagement and shopping experiences. Smart retail solutions leverage these technologies to provide interactive and personalized services. However, existing methods often suffer from inaccurate object recognition, slow processing, and lack of real-time adaptability, limiting their effectiveness in dynamic retail environments. To address these challenges, an AR-Based Object Recognition (AR-OR) framework that integrates YOLO for fast and precise object detection and Generative Adversarial Networks (GANs) for enhancing visual realism is proposed. This approach enables real-time product identification, virtual try-ons, and interactive recommendations. The proposed method significantly improves recognition accuracy, system responsiveness, and user interaction quality. Experimental results demonstrate that our framework enhances object detection speed by 30% and recognition accuracy by 25%, leading to a seamless and immersive shopping experience, ultimately transforming the future of smart retail.