Phoenix Precision Algorithm for Blind People With Enhanced Voice Assistant
Judy Flavia B., S. Sridevi, V Sai Srivathsan, Aravindak Kumar R. K., Ashwin Kumar M. K., S. Rubin Bose, R. Regin · Advances in computational intelligence and robotics book series · 2023
The chapter presents an innovative approach to object detection that combines the advantages of the DETR (DEtection TRansformer) and RetinaNet models and features a phoenix precision algorithm. Object tracking is a basic computer vision task for identifying and locating objects in an image. The DETR model revolutionized object detection by introducing a transformer-based architecture that eliminates the need for anchor boxes rather than maximum damping, resulting in industry-leading performance. On the other hand, RetinaNet is a popular single-stage object detection model known for its efficiency and accuracy. This chapter proposes a hybrid model that uses both DETR and RetinaNet. The transformer-based architecture of the DETR model provides an excellent understanding of the overall context and allows you to capture long-range dependencies and maintain object associations. Meanwhile, RetinaNet's pyramid array (FPN) and focus loss enable precise localization and manipulation of objects at different scales.