no code implementations • 4 May 2024 • Linjie Yan, Pia Addabbo, Nicomino Fiscante, Carmine Clemente, Chengpeng Hao, Gaetano Giunta, Danilo Orlando
This paper deals with the problem of clustering data returned by a radar sensor network that monitors a region where multiple moving targets are present.
no code implementations • 15 Apr 2024 • Mikolaj Czerkawski, Fraser Stewart, Christos Ilioudis, Craig Michie, Ivan Andonovic, Robert Atkinson, Maurice Coull, Donald Sandilands, Gareth Kerr, Carmine Clemente, Christos Tachtatzis
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.
no code implementations • 15 Apr 2024 • Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente, Craig Michie, Ivan Andonovic, Christos Tachtatzis
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.
no code implementations • 12 Apr 2024 • Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente, Craig Michie, Ivan Andonovic, Christos Tachtatzis
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.
no code implementations • 12 Apr 2024 • Mikolaj Czerkawski, Carmine Clemente, Craig Michie, Christos Tachtatzis
Convolutional neural networks have often been proposed for processing radar Micro-Doppler signatures, most commonly with the goal of classifying the signals.
no code implementations • 12 Apr 2024 • Mikolaj Czerkawski, Christos Ilioudis, Carmine Clemente, Craig Michie, Ivan Andonovic, Christos Tachtatzis
A novel approach to the removal of interference through the use of a probabilistic deep learning model is presented.
no code implementations • 21 Feb 2024 • Mikolaj Czerkawski, Carmine Clemente, Craig Michie, Christos Tachtatzis
Both small temporal shifts and adversarial examples are a result of a model overfitting on features that do not generalize well.
no code implementations • 2 Dec 2021 • Mikolaj Czerkawski, Javier Cardona, Robert Atkinson, Craig Michie, Ivan Andonovic, Carmine Clemente, Christos Tachtatzis
A variety of compression methods based on encoding images as weights of a neural network have been recently proposed.
no code implementations • 29 Sep 2021 • Mikolaj Czerkawski, Javier Cardona, Robert Atkinson, Craig Michie, Ivan Andonovic, Carmine Clemente, Christos Tachtatzis
Coordinate-based Multilayer Perceptron (MLP) networks, despite being capable of learning neural implicit representations, are not performant for internal image synthesis applications.
no code implementations • 21 Jun 2021 • Pia Addabbo, Filippo Biondi, Carmine Clemente, Sudan Han, Danilo Orlando, Giuseppe Ricci
This paper addresses the challenge of classifying polarimetric SAR images by leveraging the peculiar characteristics of the polarimetric covariance matrix (PCM).
no code implementations • 7 Dec 2020 • Filippo Biondi, Pia Addabbo, Carmine Clemente, Danilo Orlando, Fabrizio Tamburini
Each OAM fast-time RADAR image is separated in frequency by using MCA.
no code implementations • 6 Aug 2020 • Pia Addabbo, Mario Luca Bernardi, Filippo Biondi, Marta Cimitile, Carmine Clemente, Danilo Orlando
The capability of human identification in specific scenarios and in a quickly and accurately manner, is a critical aspect in various surveillance applications.
no code implementations • 10 Jul 2020 • Filippo Biondi, Pia Addabbo, Carmine Clemente, Silvia Liberata Ullo, Danilo Orlando
In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures.
no code implementations • 7 Apr 2014 • Carmine Clemente, Luca Pallotta, Ian Proudler, Antonio De Maio, John J. Soraghan, Alfonso Farina
The capability to exploit multiple sources of information is of fundamental importance in a battlefield scenario.