Wireless Imaging with Analog Network Coding

This lecture delves into the innovative concept of analog network coding, which leverages wireless signals to capture human poses and even images in challenging scenarios like fog or occlusions. By combining temporal information and deep neural networks, it becomes possible to reconstruct human skeletons and even track multiple individuals. The application extends to self-driving cars, where wireless signals can penetrate adverse weather conditions to aid in imaging. The instructor also touches on the future transition of the course to an eight-credit format, aiming to reduce the workload for students. Overall, the lecture showcases the potential of wireless signals in enabling imaging capabilities beyond traditional vision-based methods.