activity
20152024
most citedInterference Motion Removal for Doppler Radar Vital Sign Detection Using Variational Encoder-Decoder Neural Network

13 citations · 34 across the 8 of their papers we have counts for

collaborators

8 papers

eess.SP2024★ 1 cited

Non-invasive Diver Respiration Rate Monitoring in Hyperbaric Lifeboat Environments using Short-Range Radar

Mikolaj Czerkawski, Fraser Stewart, Christos Ilioudis +8

The monitoring of diver health during emergency events is crucial to ensuring the safety of personnel. A non-invasive system continuously providing a measure of the respiration rat…

eess.SP2024★ 4 cited

On Models and Approaches for Human Vital Signs Extraction from Short Range Radar Signals

Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente +3

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. It is shown that t…

eess.SP2024★ 4 cited

A Novel Micro-Doppler Coherence Loss for Deep Learning Radar Applications

Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente +3

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 represe…

cs.CV2024★ 13 cited

Interference Motion Removal for Doppler Radar Vital Sign Detection Using Variational Encoder-Decoder Neural Network

Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente +3

The treatment of interfering motion contributions remains one of the key challenges in the domain of radar-based vital sign monitoring. Removal of the interference to extract the v…

cs.CV2024★ 1 cited

On Input Formats for Radar Micro-Doppler Signature Processing by Convolutional Neural Networks

Mikolaj Czerkawski, Carmine Clemente, Craig Michie +1

Convolutional neural networks have often been proposed for processing radar Micro-Doppler signatures, most commonly with the goal of classifying the signals. The majority of works…

cs.CV2024★ 9 cited

Robustness of Deep Neural Networks for Micro-Doppler Radar Classification

Mikolaj Czerkawski, Carmine Clemente, Craig Michie +1

With the great capabilities of deep classifiers for radar data processing come the risks of learning dataset-specific features that do not generalize well. In this work, the robust…

physics.data-an2017★ 2 cited

Monitoring crystal breakage in wet milling processes using inline imaging and chord length distribution measurements

Okpeafoh S. Agimelen, Vaclav Svoboda, Bilal Ahmed +11

The success of the various secondary operations involved in the production of particulate products depends on the production of particles with a desired size and shape from a previ…

physics.data-an2015

Integration of in situ Imaging and Chord Length Distribution Measurements for Estimation of Particle Size and Shape

Okpeafoh S. Agimelen, Anna Jawor-Baczynska, John McGinty +5

Efficient processing of particulate products across various manufacturing steps requires that particles possess desired attributes such as size and shape. Controlling the particle…