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Sensor Signal and Information Processing II
This Special Issue compiles a set of innovative developments on the use of sensor signals and information processing. In particular, these contributions report original studies on a wide variety of sensor signals including wireless communication, machinery, ultrasound, imaging, and internet data, an...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374271/ https://www.ncbi.nlm.nih.gov/pubmed/32635516 http://dx.doi.org/10.3390/s20133751 |
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author | Woo, Wai Lok Gao, Bin |
author_facet | Woo, Wai Lok Gao, Bin |
author_sort | Woo, Wai Lok |
collection | PubMed |
description | This Special Issue compiles a set of innovative developments on the use of sensor signals and information processing. In particular, these contributions report original studies on a wide variety of sensor signals including wireless communication, machinery, ultrasound, imaging, and internet data, and information processing methodologies such as deep learning, machine learning, compressive sensing, and variational Bayesian. All these devices have one point in common: These algorithms have incorporated some form of computational intelligence as part of their core framework in problem solving. They have the capacity to generalize and discover knowledge for themselves, learning to learn new information whenever unseen data are captured. |
format | Online Article Text |
id | pubmed-7374271 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73742712020-08-05 Sensor Signal and Information Processing II Woo, Wai Lok Gao, Bin Sensors (Basel) Editorial This Special Issue compiles a set of innovative developments on the use of sensor signals and information processing. In particular, these contributions report original studies on a wide variety of sensor signals including wireless communication, machinery, ultrasound, imaging, and internet data, and information processing methodologies such as deep learning, machine learning, compressive sensing, and variational Bayesian. All these devices have one point in common: These algorithms have incorporated some form of computational intelligence as part of their core framework in problem solving. They have the capacity to generalize and discover knowledge for themselves, learning to learn new information whenever unseen data are captured. MDPI 2020-07-04 /pmc/articles/PMC7374271/ /pubmed/32635516 http://dx.doi.org/10.3390/s20133751 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Editorial Woo, Wai Lok Gao, Bin Sensor Signal and Information Processing II |
title | Sensor Signal and Information Processing II |
title_full | Sensor Signal and Information Processing II |
title_fullStr | Sensor Signal and Information Processing II |
title_full_unstemmed | Sensor Signal and Information Processing II |
title_short | Sensor Signal and Information Processing II |
title_sort | sensor signal and information processing ii |
topic | Editorial |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7374271/ https://www.ncbi.nlm.nih.gov/pubmed/32635516 http://dx.doi.org/10.3390/s20133751 |
work_keys_str_mv | AT woowailok sensorsignalandinformationprocessingii AT gaobin sensorsignalandinformationprocessingii |