mmWave Radar
Millimeter-wave (mmWave) radar is a sensing technology leveraging radio waves to perceive the environment, offering advantages in challenging conditions like low light or inclement weather, while maintaining privacy. Current research focuses on improving data processing and feature extraction using deep learning models, such as diffusion models and convolutional neural networks, to enhance applications like object recognition, human pose estimation, and motion tracking. These advancements are driving significant progress in robotics, autonomous driving, and human-computer interaction, enabling more robust and reliable systems in diverse and demanding scenarios.
Papers
A Systematic Study on Object Recognition Using Millimeter-wave Radar
Maloy Kumar Devnath, Avijoy Chakma, Mohammad Saeid Anwar, Emon Dey, Zahid Hasan, Marc Conn, Biplab Pal, Nirmalya Roy
Improved Static Hand Gesture Classification on Deep Convolutional Neural Networks using Novel Sterile Training Technique
Josiah Smith, Shiva Thiagarajan, Richard Willis, Yiorgos Makris, Murat Torlak