International Research Journal of Education and Technology

Face detection is a critical component of modern computer vision systems, with applications spanning security, surveillance, biometrics, and human-computer interaction. This study presents a high-performance face detection system optimized for deployment on NVIDIA Jetson platforms, renowned for their efficiency in edge computing and artificial intelligence (AI) applications. The proposed system leverages state-of-the-art deep learning techniques, employing models such as YOLO (You Only Look Once), SSD (Single Shot MultiBox Detector), or MTCNN (Multi-task Cascaded Convolutional Networks), which are fine-tuned to deliver high accuracy in diverse real-world scenarios. The NVIDIA Jetson platform, encompassing devices like Jetson Nano, Xavier, and Orin, provides a powerful yet compact solution for real-time inference.

For instance, the Jetson Nano supports 1080p video feeds at 30 frames per second with minimal latency, while the Jetson Xavier and Orin extend this capability to 4K video streams. This scalability ensures the system’s applicability across a range of use cases, from small-scale residential security to large-scale industrial surveillance.

Keywords: Jetson Nano ,Face detection,artificial intelligence