Bearing estimation of low probability of intercept sources via polynomial matrices and sparse linear arrays

Autor: William Coventry, Carmine Clemente, John Soraghan, Neil Cade

Publikováno v: IET Radar, Sonar & Navigation, Vol 15, Iss 11, Pp 1408-1419 (2021)

Abstract Recent years have seen a steady convergence of Radar and Communications band Radio Frequency (RF) transceiver systems. Not only have Communications systems colonised large swathes of previously allocated Radar bands but there is also a conve

Externí odkaz: https://doaj.org/article/19c89d436ae34557823d212ccd0692d2

Perception Understanding Action: Adding Understanding to the Perception Action Cycle With Spiking Segmentation

Autor: Paul Kirkland, Gaetano Di Caterina, John Soraghan, George Matich

Publikováno v: Frontiers in Neurorobotics, Vol 14 (2020)

Traditionally the Perception Action cycle is the first stage of building an autonomous robotic system and a practical way to implement a low latency reactive system within a low Size, Weight and Power (SWaP) package. However, within complex scenarios

Externí odkaz: https://doaj.org/article/a60a374b77874a3b9da26b6f1c0ac762

A Music Cognition–Guided Framework for Multi-pitch Estimation

Autor: Xiaoquan Li, Yijun Yan, John Soraghan, Zheng Wang, Jinchang Ren

Publikováno v: Cognitive Computation. 15:23-35

As one of the most important subtasks of automatic music transcription (AMT), multi-pitch estimation (MPE) has been studied extensively for predicting the fundamental frequencies in the frames of audio recordings during the past decade. However, how

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::401b2e7233a94147b3a15000303fa718
https://doi.org/10.1007/s12559-022-10031-5

Polarimetric information to enhance synthetic aperture radar automatic target recognition capabilities

Autor: Domenico Gaglione, Carmine Clemente, Luca Pallotta, Christos Ilioudis, Antonio De Maio, John Soraghan

Publikováno v: Polarimetric Radar Signal Processing ISBN: 9781839534027

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b62c634058ef28d38856ae708414b4ba
https://doi.org/10.1049/sbra549e_ch6

A U-Net Based Multi-scale Feature Extraction for Liver Tumour Segmentation in CT Images

Autor: Ming Gong, John Soraghan, Gaetano Di Caterina, Derek Grose

Publikováno v: Lecture Notes in Electrical Engineering ISBN: 9789811903892
Lecture Notes in Electrical Engineering ISBN: 9789811903854
University of Strathclyde

A new method for automatic liver tumour segmentation from computed tomography (CT) scans based on deep neural network is presented. Two cascaded deep convolu-tional neural networks are used to segment the CT image of the abdominal cavity. The first U

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::001c0c1ef093aacbb44d05983caafc1b
https://doi.org/10.1007/978-981-19-0390-8_127