[HTML][HTML] Dynamic Gesture Recognition Based on FMCW Millimeter Wave Radar: Review of Methodologies and Results

G Tang, T Wu, C Li - Sensors, 2023 - mdpi.com
As a convenient and natural way of human-computer interaction, gesture recognition
technology has broad research and application prospects in many fields, such as intelligent …

End-to-end dynamic gesture recognition using mmWave radar

A Ali, P Parida, V Va, S Ni, KN Nguyen, BL Ng… - IEEE …, 2022 - ieeexplore.ieee.org
Millimeter-wave (mmWave) radar sensors are a promising modality for gesture recognition
as they can overcome several limitations of optic sensors typically used for gesture …

Analysis of User-defined Radar-based Hand Gestures Sensed through Multiple Materials

A Sluÿters, S Lambot, J Vanderdonckt… - IEEE …, 2024 - ieeexplore.ieee.org
Radar sensing can penetrate non-conducting materials, such as glass, wood, and plastic,
which makes it appropriate for recognizing gestures in environments with poor visibility …

[HTML][HTML] Context-adaptable radar-based people counting via few-shot learning

G Mauro, I Martinez-Rodriguez, J Ott, L Servadei… - Applied …, 2023 - Springer
In many industrial or healthcare contexts, keeping track of the number of people is essential.
Radar systems, with their low overall cost and power consumption, enable privacy-friendly …

MMHTSR: In-Air Handwriting Trajectory Sensing and Reconstruction Based on mmWave Radar

Q Chen, Z Cui, Z Zhou, Y Tian… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
In-air handwriting necessitates consistent motion tracking, in contrast to millimeter-wave
(mmWave) radar-based simple gesture recognition techniques. However, during long …

Lightweight Online Semisupervised Learning for Ultrasonic Radar-Based Dynamic Hand Gesture Recognition

P Kang, X Li - IEEE Sensors Journal, 2022 - ieeexplore.ieee.org
Ultrasonic dynamic hand gesture recognition (U-DHGR) is a promising approach of human–
computer interaction (HCI) for a broad range of emerging applications. Cross-user …

Temporal Patience: Efficient Adaptive Deep Learning for Embedded Radar Data Processing

M Sponner, J Ott, L Servadei, B Waschneck… - arXiv preprint arXiv …, 2023 - arxiv.org
Radar sensors offer power-efficient solutions for always-on smart devices, but processing
the data streams on resource-constrained embedded platforms remains challenging. This …

Fast Learning of Dynamic Hand Gesture Recognition with Few-Shot Learning Models

N Schlüsener, M Bücker - arXiv preprint arXiv:2212.08363, 2022 - arxiv.org
We develop Few-Shot Learning models trained to recognize five or ten different dynamic
hand gestures, respectively, which are arbitrarily interchangeable by providing the model …

[HTML][HTML] LaANIL: ANIL with Look-Ahead Meta-Optimization and Data Parallelism

V Tammisetti, K Bierzynski, G Stettinger… - Electronics, 2024 - mdpi.com
Meta-few-shot learning algorithms, such as Model-Agnostic Meta-Learning (MAML) and
Almost No Inner Loop (ANIL), enable machines to learn complex tasks quickly with limited …

[PDF][PDF] ROZPRAWA DOKTORSKA

P Reczek, KR i Mechatroniki - eaiib.agh.edu.pl
Niniejsza praca przedstawia nowe metody rozpoznawania gestów 3D bez użycia kamer, w
aplikacjach w branży motoryzacyjnej. W ramach realizacji pracy, dokonano przeglądu …