Visionary Text Recognition System for Assisting the Visually Impaired in Identifying Medicines and Products with Hybrid Deep Learning

This research focuses on developing an assistive technology for visually impaired individuals, enabling them to read text and recognize objects in their environment. The system utilizes a camera-based approach, employing a ResNet model for object detection and text recognition. The proposed system aims to accurately identify and classify objects in real-time, providing audio feedback to the user. This technology can be particularly beneficial for visually impaired individuals in various daily life scenarios, such as reading medication labels, identifying objects in their surroundings, and navigating public spaces. By integrating advanced computer vision techniques, this research aims to improve the quality of life for visually impaired individuals by enhancing their independence and autonomy.