scholarly journals Editorial for the Special Issue “Advanced Artificial Intelligence and Deep Learning for Remote Sensing”

2021 ◽  
Vol 13 (15) ◽  
pp. 2883
Author(s):  
Gwanggil Jeon
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Deep Learning ◽  
Special Issue ◽  
The Earth

Remote sensing is a fundamental tool for comprehending the earth and supporting human–earth communications [...]

scholarly journals Editorial of Special Issue “Machine and Deep Learning for Earth Observation Data Analysis”

2021 ◽  
Vol 13 (14) ◽  
pp. 2758
Author(s):  
Vasileios Syrris ◽  
Sveinung Loekken
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Data Analysis ◽  
Earth Observation ◽  
Observation Data ◽  
Earth System ◽  
Special Issue ◽  
The Earth ◽  
Comprehensive Information ◽  
Earth Observation Data

Earth observation and remote sensing technologies provide ample and comprehensive information regarding the dynamics and complexity of the Earth system [...]

scholarly journals Editorial: Special Issue “Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems”

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6383
Author(s):  
Sigfredo Fuentes ◽  
Eden Jane Tongson
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Sensor Networks ◽  
Internet Of Things ◽  
Urban Agriculture ◽  
Environmental Hazards ◽  
Special Issue ◽  
Hazards Assessment ◽  
Editorial Special Issue

Artificial intelligence (AI), together with robotics, sensors, sensor networks, internet of things (IoT) and machine/deep learning modeling, has reached the forefront towards the goal of increased efficiency in a multitude of application and purpose [...]

scholarly journals Computational Intelligence in Remote Sensing: An Editorial

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 633
Author(s):  
Manuel Graña ◽  
Michal Wozniak ◽  
Sebastian Rios ◽  
Javier de Lope
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Data Analysis ◽  
Computational Intelligence ◽  
Wide Spectrum ◽  
Remote Sensing Data ◽  
Research Development ◽  
Special Issue ◽  
Computational Tools ◽  
Fruitful Research

Computational intelligence is a very active and fruitful research of artificial intelligence with a broad spectrum of applications. Remote sensing data has been a salient field of application of computational intelligence algorithms, both for the exploitation of the data and for the research/ development of new data analysis tools. In this editorial paper we provide the setting of the special issue “Computational Intelligence in Remote Sensing” and an overview of the published papers. The 11 accepted and published papers cover a wide spectrum of applications and computational tools that we try to summarize and put in perspective in this editorial paper.

scholarly journals Editorial for Special Issue “Earth Radiation Budget”

2020 ◽  
Vol 12 (20) ◽  
pp. 3379
Author(s):  
Steven Dewitte
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Radiation Budget ◽  
Climate Data ◽  
Special Issue ◽  
The Earth ◽  
Earth Radiation Budget ◽  
Term Monitoring ◽  
Earth Radiation

The Earth Radiation Budget (ERB) at the top of the atmosphere describes how the Earth gains energy from the Sun and loses energy to space through the reflection of solar radiation and the emission of thermal radiation. The ERB is measured from space with dedicated remote sensing instruments. Its long-term monitoring is of fundamental importance for understanding climate change. This Special Issue contains contributions focusing on ERB remote sensing instruments for either (1) the establishment of past and current ERB Climate Data Records (CDRs), (2) insights in climate change gained from the analysis of ERB CDRs, and 3) the outlook for continued or improved future ERB monitoring.

scholarly journals Special Issue “Advanced Signal Processing in Intelligent Systems for Health Monitoring”

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4727
Author(s):  
Maysam Abbod ◽  
Jiann-Shing Shieh
Keyword(s):  
Artificial Intelligence ◽  
Signal Processing ◽  
Big Data ◽  
Deep Learning ◽  
Health Monitoring ◽  
Intelligent Systems ◽  
Measurement Techniques ◽  
Mechanical Systems ◽  
Data Sets ◽  
Special Issue

Recently, significant developments have been achieved in the field of artificial intelligence, in particular the introduction of deep learning technology that has improved the learning and prediction accuracy to unpresented levels, especially when dealing with big data and high-resolution images. Significant developments have occurred in the area of medical signal processing, measurement techniques, and health monitoring, such as vital biological signs for biomedical systems and noise and vibration of mechanical systems, which are carried out by instruments that generate large data sets. These big data sets, ultimately driven by high population growth, would require Artificial Intelligence techniques to analyse and model. In this Special Issue, papers are presented on the latest signal processing and deep learning techniques used for health monitoring of biomedical and mechanical systems.

scholarly journals Introduction to the TPLP Special Issue on User-oriented Logic Programming and Reasoning Paradigms

2019 ◽  
Vol 19 (2) ◽  
pp. 109-113
Author(s):  
STEFAN ELLMAUTHALER ◽  
CLAUDIA SCHULZ
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Knowledge Representation ◽  
Logic Programming ◽  
Unstructured Data ◽  
Knowledge Representation And Reasoning ◽  
Special Issue

With the rise of machine learning, and more recently the overwhelming interest in deep learning, knowledge representation and reasoning (KRR) approaches struggle to maintain their position within the wider Artificial Intelligence (AI) community. Often considered as part of thegood old-fashioned AI(Haugeland 1985) – like a memory of glorious old days that have come to an end – many consider KRR as no longer applicable (on its own) to the problems faced by AI today (Blackwell 2015; Garneloet al.2016). What they see are logical languages with symbols incomprehensible by most, inference mechanisms that even experts have difficulties tracing and debugging, and the incapability to process unstructured data like text.

scholarly journals Radar and Sonar Imaging and Processing (2nd Edition)

2021 ◽  
Vol 13 (22) ◽  
pp. 4656
Author(s):  
Andrzej Stateczny ◽  
Witold Kazimierski ◽  
Krzysztof Kulpa
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Special Issue ◽  
Imaging Processing ◽  
Sonar Sensors ◽  
Sonar Imaging ◽  
Sonar Images

The 14 papers (from 29 submitted) published in the Special Issue “Radar and Sonar Imaging Processing (2nd Edition)” highlight a variety of topics related to remote sensing with radar and sonar sensors. The sequence of articles included in the SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends, in which the latest developments in science, including artificial intelligence, were used.

scholarly journals Explainable data fusion

2021 ◽  
Author(s):  
◽  
Bryce J. Murray
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Deep Learning ◽  
Data Fusion ◽  
Case Studies ◽  
Information Fusion ◽  
Human Life ◽  
Fuzzy Integral ◽  
Highly Educated ◽  
Explainable Ai

The recent resurgence of Artificial Intelligence (AI), specifically in the context of applications like healthcare, security and defense, IoT, and other areas that have a big impact on human life, has led to a demand for eXplainable AI (XAI). The production of explanations is argued to be a key aspect of achieving goals like trustworthiness and transparent versus opaque AI. XAI is also of fundamental academic interest with respect to helping us identifying weaknesses in the pursuit of making better AI. Herein, I focus on one piece of the AI puzzle, information fusion. In this work, I propose XAI fusion indices, linguistic summaries (aka textual explanations) of these indices, and local explanations for the fuzzy integral. However, a limitation of these indices is its tailored to highly educated fusion experts, and it is not clear what to do with these explanations. Herein, I extend the introduced indices to actionable explanations, which are demonstrated in the context of two case studies; multi-source fusion and deep learning for remote sensing. This work ultimately shows what XAI for fusion is and how to create actionable insights.

scholarly journals Editorial for Special Issue “Remote Sensing for Monitoring Wildlife and Habitat in a Changing World”

2021 ◽  
Vol 13 (14) ◽  
pp. 2762
Author(s):  
Andrés Viña
Keyword(s):  
Remote Sensing ◽  
Human Impacts ◽  
Special Issue ◽  
The Earth ◽  
Changing World

Escalating human impacts on the Earth are creating unprecedented challenges, including the drastic degradation and loss of biodiversity worldwide [...]

scholarly journals Remote Sensing in Vessel Detection and Navigation

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5841
Author(s):  
Henning Heiselberg ◽  
Andrzej Stateczny
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Special Issue ◽  
Vessel Detection

The Special Issue (SI) “Remote Sensing in Vessel Detection and Navigation” highlighted a variety of topics related to remote sensing with navigational sensors. The sequence of articles included in this Special Issue is in line with the latest scientific trends. The latest developments in science, including artificial intelligence, were used. The 15 papers (from 23 submitted) were published.

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