Self-supervised contrastive learning for radar-based human activity recognition

MM Rahman, SZ Gurbuz - 2023 IEEE Radar Conference …, 2023 - ieeexplore.ieee.org
Short-range radars are widely used for micro-Doppler-based human activity recognition by
using the super-vised training paradigm. However, acquiring labeled trained RF data is not …

Super-resolution radar imaging with sparse arrays using a deep neural network trained with enhanced virtual data

C Schuessler, M Hoffmann… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
This paper introduces a method based on a deep neural network (DNN) that is perfectly
capable of processing radar data from extremely thinned radar apertures. The proposed …

[HTML][HTML] An acoustic tracking model based on deep learning using two hydrophones and its reverberation transfer hypothesis, applied to whale tracking

K Jin, J Xu, X Zhang, C Lu, L Xu, Y Liu - Frontiers in Marine Science, 2023 - frontiersin.org
Acoustic tracking of whales' underwater cruises is essential for protecting marine
ecosystems. For cetacean conservationists, fewer hydrophones will provide more …

Look, Radiate, and Learn: Self-Supervised Localisation via Radio-Visual Correspondence

M Alloulah, M Arnold - … of the IEEE/CVF Conference on …, 2023 - openaccess.thecvf.com
Next generation cellular networks will implement radio sensing functions alongside
customary communications, thereby enabling unprecedented worldwide sensing coverage …

[图书][B] Deep Scene Understanding using RF and its Fusion with other Modalities

AD Singh - 2023 - search.proquest.com
Rich scene understanding is a critical first step in creating autonomous systems with
situational awareness–ie systems that can not only perceive and comprehend their …

[PDF][PDF] A Survey of MIMO Schemes and Processing Chain for Automotive Radars

G Solodky - researchgate.net
To achieve the radar strengths, such as high detection range, robustness to adverse
weather, and the ability to directly estimate the relative radial velocity, the transmit regime …