Dynamic Gender Recognition using YOLOv7 with Minimal Frame per Second

Gender recognition is an essential component of computer vision applications, with numerous real-world applications. This research paper explores the development and implementation of a dynamic gender recognition system using YOLOv7 (You Only Look Once version 7) with a focus on achieving minimal frames per second (FPS). We investigate the methodology, data preprocessing, model architecture, and real-world applications of this system, emphasizing its potential for efficient gender recognition in dynamic settings.