JEDAN: Joint Euclidean Distance and Autoencoder Network for Robust Out-of-Distribution Detection in Radar-Based Hand Gesture Recognition

Detecting Out-of-Distribution (OOD) gestures is vital for reliable radar-based gesture-recognition systems. Traditional autoencoders often fall short in OOD detection because they prioritize minimizing reconstruction error over forming distinct clusters in the latent space. This study proposes Joint...

Повний опис

Бібліографічні деталі

Автори:	Muhammad Ghufran Janjua, Kevin Kaiser, Thomas Stadelmayer, Stephan Schoenfeldt, Vadim Issakov
Формат:	Artigo
Мова:	Inglês
Опубліковано:	IEEE 2024-01-01
Серія:	IEEE Access
Предмети:	Artificial neural networks autoencoders deep learning FMCW radar gesture recognition out-of-distribution detection
Онлайн доступ:	https://ieeexplore.ieee.org/document/10810384/
Теги:	Додати тег Немає тегів, Будьте першим, хто поставить тег для цього запису!