Artificial Intelligence and Sensing Technologies Based Astrophysics and Applications
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 13877
Special Issue Editors
Interests: medical image processing
2. Departamento de Astrofísica, Universidad de La Laguna, La Laguna, Spain
Interests: telescopes; optical and infrared instrumentation; gravitational lensing; small satellites; remote sensing; high spatial resolution
2. Department of Electronics, Norwagian University of Science and Technology, Norway
Interests: Small Satellites; Systems Engineering; Constellations; Communications Systems; Remote Sensing; Model Based Systems Engineering
Special Issue Information
Dear Colleagues,
Astrophysics is a major branch of science that relies on advanced and innovative technology. In particular, imaging and image data processing are cornerstones for the development of the field. More recently artificial intelligence and, in particular, machine and deep learning have become key to facilitate the understanding of such complex big data as that provided by modern observation instruments. Technology innovations in Astrophysics have traditionally sparked further innovations in many other fields and application domains. The main goal of this special issue is to promote cross-fertilization between astrophysics technology and other fields, such as remote sensing, aerospace, unmanned vehicles, and medical imaging by leveraging recent advances in artificial intelligence and sensing technologies.
We solicit manuscripts of both review and original research articles in all the aspects pertinent to this Special Issue on “Artificial Intelligence and Sensing Technologies Based Astrophysics and Applications”. Topics of interest include, but are not limited to, the following:
- Imaging. Light is the main tool, and in most of the occasions the only one, for astrophysicists. One of the main objectives of observational astronomy is to detect faint targets, as weak as possible, and to be able to discriminate their details. However, desirable resolution is not always obtained and, therefore, for many years, astronomers have struggled to offer diffraction-limited imaging using techniques such as adaptive optics, lucky imaging or image postprocessing. The developments in astronomy involve some cutting-edge technologies and knowledge that can be exported to other different fields; mainly, but not limited, to the medical and biomedical sectors. In this issue, we invite researchers to present techniques used in and from astrophysics to improve the quality of images, including the cross-fusion of remote sensing images, hyperspectral images, medical images and other images with astrophysical technologies. Additionally, due to the unprecedented situation that the unfolding COVID-19 pandemic is causing World-wide, we make a special call to solicit research articles where deep learning (or, in general, machine learning) enabled biomedical sensing might help to monitor and control the spread of the disease and to mitigate its effects. For example:
- Camera-based (thermal, NIR, visible, etc) distant monitoring of biomedical parameters
- Machine-learning based biomarker extraction for triage, screening and diagnosis
- Aerospace, unmanned vehicles and remote sensing: In this special issue, we make a special call to present research contributions based on astrophysics technologies and algorithms that have been or potentially apply to space applications as well unmanned vehicles, especially in the area of remote sensing. Also are welcome contributions presenting technologies and artificial algorithms used in remote sensing and aerospace areas that can apply to astrophysics research problems.
- Artificial intelligence, machine learning, deep learning, as related to imaging and sensing applications: Artificial Intelligence is rapidly becoming a standard approach to process images in many fields of fundamental and applied research including astrophysics. It is used for a variety of purposes going from simple classification tasks to more complex segmentation, regression, tracking or even unsupervised generation and anomaly detection. In recent years, astrophysics research has widely benefited from the artificial intelligence revolution. On the other side, because of the specific properties of astrophysical data (e.g. low S/N, high dynamic range), applications to astrophysics can also induce new progress in the fields of machine learning and computer science by better probing the limits of the different techniques. We are precisely interested in this issue in exploring this cross-fertilization between the two fields.
Promoting science and technology cross-fertilization between Astrophysics and other fields is the main goal of this special issue, with a particular focus on imaging, sensing and artificial intelligence. Therefore, authors must clearly show how their research leverages synergies among astrophysics technology and other fields or what the potential cross-impact may be.
Prof. Juan Ruiz-Alzola
Dr. Alejandro Oscoz Abad
Prof. Dr. Fernando Aguado Agelet
Dr. Marc Huertas-Company
Guest Editors
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Keywords
- Imaging
- Artificial intelligence
- Deep learning
- Astrophysics
- Imaging in Astrophysics
- Adaptive optics
- Signal and Image Processing Techniques
- Remote Sensing
- Satellite Applications
- Constellations
- Unmanned Vehicles applications
- Medical Imaging
- Medical Image Computing
- COVID-19
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