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Found 9 papers, 0 papers with code
Non-invasive Diver Respiration Rate Monitoring in Hyperbaric Lifeboat Environments using Short-Range Radar
Further, evidence is provided that the radar-based approach yields a more accurate measure of respiration rate than an audio signal from a headset microphone.
On Models and Approaches for Human Vital Signs Extraction from Short Range Radar Signals
The paper centres on an assessment of the modelling approaches for the processing of signals in CW and FMCW radar-based systems for the detection of vital signs.
Interference Motion Removal for Doppler Radar Vital Sign Detection Using Variational Encoder-Decoder Neural Network
A novel approach to the removal of interference through the use of a probabilistic deep learning model is presented.
On Input Formats for Radar Micro-Doppler Signature Processing by Convolutional Neural Networks
Convolutional neural networks have often been proposed for processing radar Micro-Doppler signatures, most commonly with the goal of classifying the signals.
A Novel Micro-Doppler Coherence Loss for Deep Learning Radar Applications
Deep learning techniques are subject to increasing adoption for a wide range of micro-Doppler applications, where predictions need to be made based on time-frequency signal representations.
Robustness of Deep Neural Networks for Micro-Doppler Radar Classification
Both small temporal shifts and adversarial examples are a result of a model overfitting on features that do not generalize well.
Neural Weight Step Video Compression
A variety of compression methods based on encoding images as weights of a neural network have been recently proposed.
Neural Knitworks: Patched Neural Implicit Representation Networks
Coordinate-based Multilayer Perceptron (MLP) networks, despite being capable of learning neural implicit representations, are not performant for internal image synthesis applications.
Leveraging Siamese Networks for One-Shot Intrusion Detection Model
Supervised ML is based upon learning by example, demanding significant volumes of representative instances for effective training and the need to re-train the model for every unseen cyber-attack class.
