Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The advent of Internet of Things offers a scalable and seamless connection of physical objects, including human beings and devices. This, along with artificial intelligence, has moved transportation towards becoming intelligent transportation. This book is a collection of eleven articles that have served as examples of the success of internet of things and artificial intelligence deployment in transportation research. Topics include collision avoidance for surface ships, indoor localization, vehicle authentication, traffic signal control, path-planning of unmanned ships, driver drowsiness and stress detection, vehicle density estimation, maritime vessel flow forecast, and vehicle license plate recognition. High-performance computing services have become more affordable in recent years, which triggered the adoption of deep-learning-based approaches to increase the performance standards of artificial intelligence models. Nevertheless, it has been pointed out by various researchers that traditional shallow-learning-based approaches usually have an advantage in applications with small datasets. The book can provide information to government officials, researchers, and practitioners. In each article, the authors have summarized the limitations of existing works and offered valuable information on future research directions.

History of engineering & technology --- decision-making --- autonomous navigation --- collision avoidance --- scene division --- deep reinforcement learning --- maritime autonomous surface ships --- internet of things --- crowdsourcing --- indoor localization --- data fusion --- security --- authentication --- Inertial Measurement Units --- road transportation --- traffic signal control --- speed guidance --- vehicle arrival time --- connected vehicle --- unmanned ships --- DDPG --- autonomous path planning --- end-to-end --- at-risk driving --- deep support vector machine --- driver drowsiness --- driver stress --- multi-objective genetic algorithm --- multiple kernel learning --- urban freeway --- hybrid dynamic system --- state transition --- unknown inputs observer --- vehicle density --- maritime vessel flows --- intelligent transportation systems --- deep learning --- automatic license plate recognition --- intelligent vehicle access --- histogram of oriented gradients --- artificial neural networks --- convolutional neural networks --- time-frequency --- Inertial Measurement Unit (IMU) --- road anomalies --- decision-making --- autonomous navigation --- collision avoidance --- scene division --- deep reinforcement learning --- maritime autonomous surface ships --- internet of things --- crowdsourcing --- indoor localization --- data fusion --- security --- authentication --- Inertial Measurement Units --- road transportation --- traffic signal control --- speed guidance --- vehicle arrival time --- connected vehicle --- unmanned ships --- DDPG --- autonomous path planning --- end-to-end --- at-risk driving --- deep support vector machine --- driver drowsiness --- driver stress --- multi-objective genetic algorithm --- multiple kernel learning --- urban freeway --- hybrid dynamic system --- state transition --- unknown inputs observer --- vehicle density --- maritime vessel flows --- intelligent transportation systems --- deep learning --- automatic license plate recognition --- intelligent vehicle access --- histogram of oriented gradients --- artificial neural networks --- convolutional neural networks --- time-frequency --- Inertial Measurement Unit (IMU) --- road anomalies

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The advent of Internet of Things offers a scalable and seamless connection of physical objects, including human beings and devices. This, along with artificial intelligence, has moved transportation towards becoming intelligent transportation. This book is a collection of eleven articles that have served as examples of the success of internet of things and artificial intelligence deployment in transportation research. Topics include collision avoidance for surface ships, indoor localization, vehicle authentication, traffic signal control, path-planning of unmanned ships, driver drowsiness and stress detection, vehicle density estimation, maritime vessel flow forecast, and vehicle license plate recognition. High-performance computing services have become more affordable in recent years, which triggered the adoption of deep-learning-based approaches to increase the performance standards of artificial intelligence models. Nevertheless, it has been pointed out by various researchers that traditional shallow-learning-based approaches usually have an advantage in applications with small datasets. The book can provide information to government officials, researchers, and practitioners. In each article, the authors have summarized the limitations of existing works and offered valuable information on future research directions.

History of engineering & technology --- decision-making --- autonomous navigation --- collision avoidance --- scene division --- deep reinforcement learning --- maritime autonomous surface ships --- internet of things --- crowdsourcing --- indoor localization --- data fusion --- security --- authentication --- Inertial Measurement Units --- road transportation --- traffic signal control --- speed guidance --- vehicle arrival time --- connected vehicle --- unmanned ships --- DDPG --- autonomous path planning --- end-to-end --- at-risk driving --- deep support vector machine --- driver drowsiness --- driver stress --- multi-objective genetic algorithm --- multiple kernel learning --- urban freeway --- hybrid dynamic system --- state transition --- unknown inputs observer --- vehicle density --- maritime vessel flows --- intelligent transportation systems --- deep learning --- automatic license plate recognition --- intelligent vehicle access --- histogram of oriented gradients --- artificial neural networks --- convolutional neural networks --- time-frequency --- Inertial Measurement Unit (IMU) --- road anomalies --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The Special Issue entitled “Remote Sensing in Vessel Detection and Navigation” comprises 15 articles on many 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. It can be said that navigation and vessel detection remain important and hot topics, and a lot of work will continue to be done worldwide. New techniques and methods for analyzing and extracting information from navigational sensors and data have been proposed and verified. Some of these will spark further research, and some are already mature and can be considered for industrial implementation and development.

Research & information: general --- autonomous navigation --- automatic radar plotting aid --- safe objects control --- game theory --- computer simulation --- Sentinel-2 --- multispectral --- temporal offsets --- ship --- aircraft --- velocity --- altitude --- parallax --- jet stream --- Unmanned Surface Vessel (USV) --- multi-Global Navigation Satellite System (GNSS) receiver --- bathymetric measurements --- cross track error (XTE) --- SSL --- six-degrees-of-freedom motion --- motion attitude model --- edge detection --- straight-line fitting --- visual saliency --- vessel detection --- video monitoring --- inland waterway --- real-time detection --- neural network --- target recognition --- HRRP --- residual structure --- loss function --- trajectory tracking --- unmanned surface vehicle --- navigation --- bathymetry --- hydrographic survey --- real-time communication --- maritime situational awareness --- ship detection --- Iridium --- on-board --- image processing --- flight campaign --- position estimation --- ranging mode --- single shore station --- AIS --- bag-of-words mechanism --- machine learning --- image analysis --- ship classification --- marine system --- river monitoring system --- feature extraction --- synthetic aperture radar (SAR) ship detection --- multi-stage rotational region based network (MSR2N) --- rotated anchor generation --- multi-stage rotational detection network (MSRDN) --- convolutional neural network (CNN) --- synthetic aperture radar (SAR) --- multiscale and small ship detection --- complex background --- false alarm --- farbon dioxide peaks --- midwave infrared --- FTIR --- adaptive stochastic resonance (ASR) --- matched intrawell response --- nonlinear filter --- line enhancer --- autonomous underwater vehicles (AUVs) --- target tracking --- group targets --- GLMB --- structure --- formation --- remote sensing --- autonomous navigation --- automatic radar plotting aid --- safe objects control --- game theory --- computer simulation --- Sentinel-2 --- multispectral --- temporal offsets --- ship --- aircraft --- velocity --- altitude --- parallax --- jet stream --- Unmanned Surface Vessel (USV) --- multi-Global Navigation Satellite System (GNSS) receiver --- bathymetric measurements --- cross track error (XTE) --- SSL --- six-degrees-of-freedom motion --- motion attitude model --- edge detection --- straight-line fitting --- visual saliency --- vessel detection --- video monitoring --- inland waterway --- real-time detection --- neural network --- target recognition --- HRRP --- residual structure --- loss function --- trajectory tracking --- unmanned surface vehicle --- navigation --- bathymetry --- hydrographic survey --- real-time communication --- maritime situational awareness --- ship detection --- Iridium --- on-board --- image processing --- flight campaign --- position estimation --- ranging mode --- single shore station --- AIS --- bag-of-words mechanism --- machine learning --- image analysis --- ship classification --- marine system --- river monitoring system --- feature extraction --- synthetic aperture radar (SAR) ship detection --- multi-stage rotational region based network (MSR2N) --- rotated anchor generation --- multi-stage rotational detection network (MSRDN) --- convolutional neural network (CNN) --- synthetic aperture radar (SAR) --- multiscale and small ship detection --- complex background --- false alarm --- farbon dioxide peaks --- midwave infrared --- FTIR --- adaptive stochastic resonance (ASR) --- matched intrawell response --- nonlinear filter --- line enhancer --- autonomous underwater vehicles (AUVs) --- target tracking --- group targets --- GLMB --- structure --- formation --- remote sensing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The Special Issue entitled “Remote Sensing in Vessel Detection and Navigation” comprises 15 articles on many 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. It can be said that navigation and vessel detection remain important and hot topics, and a lot of work will continue to be done worldwide. New techniques and methods for analyzing and extracting information from navigational sensors and data have been proposed and verified. Some of these will spark further research, and some are already mature and can be considered for industrial implementation and development.

autonomous navigation --- automatic radar plotting aid --- safe objects control --- game theory --- computer simulation --- Sentinel-2 --- multispectral --- temporal offsets --- ship --- aircraft --- velocity --- altitude --- parallax --- jet stream --- Unmanned Surface Vessel (USV) --- multi-Global Navigation Satellite System (GNSS) receiver --- bathymetric measurements --- cross track error (XTE) --- SSL --- six-degrees-of-freedom motion --- motion attitude model --- edge detection --- straight-line fitting --- visual saliency --- vessel detection --- video monitoring --- inland waterway --- real-time detection --- neural network --- target recognition --- HRRP --- residual structure --- loss function --- trajectory tracking --- unmanned surface vehicle --- navigation --- bathymetry --- hydrographic survey --- real-time communication --- maritime situational awareness --- ship detection --- Iridium --- on-board --- image processing --- flight campaign --- position estimation --- ranging mode --- single shore station --- AIS --- bag-of-words mechanism --- machine learning --- image analysis --- ship classification --- marine system --- river monitoring system --- feature extraction --- synthetic aperture radar (SAR) ship detection --- multi-stage rotational region based network (MSR2N) --- rotated anchor generation --- multi-stage rotational detection network (MSRDN) --- convolutional neural network (CNN) --- synthetic aperture radar (SAR) --- multiscale and small ship detection --- complex background --- false alarm --- farbon dioxide peaks --- midwave infrared --- FTIR --- adaptive stochastic resonance (ASR) --- matched intrawell response --- nonlinear filter --- line enhancer --- autonomous underwater vehicles (AUVs) --- target tracking --- group targets --- GLMB --- structure --- formation --- remote sensing

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The Special Issue “Radar and Sonar Imaging Processing” is a collection of 21 articles exploring many topics related to remote sensing with radar and sonar sensors. In this editorial, we present short introductions of the published articles. The series of articles in this SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends while making use of the latest developments in science, including artificial intelligence. It can be said that both radar and sonar imaging and processing still remain a “hot topic” and much research in this area is being conducted worldwide. New techniques and methods for extracting information from radar and sonar sensors and data have been proposed and verified. Some of these will stimulate further research while others have reached maturity and can be considered for industrial implementation and development.

radar --- fuzzy sets theory --- artificial neural network --- game theory --- safe ship trajectory --- computer simulation --- computer decision support --- underwater sonar image --- adaptive denoising --- detection --- adaptive initialization --- synthetic aperture sonar (SAS) --- multireceiver --- numerical evaluation --- numerical transfer function --- imaging algorithm --- X-Band radar --- marine radar current measurement --- quality control --- measurement reliability --- accuracies --- precision --- WaMoS® II --- vessel mounted acoustic Doppler current profiler --- autonomous surface vehicles --- anti-collision --- automotive radar --- target detection --- interferometric inverse synthetic aperture radar (InISAR) --- image registration --- translational motion parameters estimation --- strong scattering centers fusion --- terahertz radar imaging --- side-scan sonar image --- gray scale correction --- Retinex --- image enhancement --- side-scan sonar --- multibeam echo sounder --- initial image matching with constraint --- dense local self-similarity --- superimposition --- quadratic phase error --- SAR --- approximation --- spaceborne real-time SAR imaging --- orbit determination error --- synthetic aperture radar (SAR) --- low frequency --- high-resolution --- large bandwidth --- improved generalized chirp scaling (GCS) --- Lagrange inversion theorem --- range-dependent coupling --- complex Doppler ambiguity --- fast-maneuvering target refocusing --- non-uniform FFT (NUFFT) --- 1D scaled Fourier transform (1D SCFT) --- 3D sonar --- bathymetry --- data reduction --- autonomous navigation --- ground penetrating radar --- underground cavity detection network --- deep convolutional neural network --- automated underground object classification --- phase analysis --- super-resolution --- anti-drone systems --- FMCW radars --- drones detection --- radars calibration --- narrow-band radar --- target classification --- signal reconstruction --- features extraction --- weighted features fusion --- Synthetic Aperture Radar (SAR) --- focusing --- periodically gapped data --- complex deconvolution --- side scan sonar --- bottom tracking --- one-dimensional convolutional neural network --- signal recognition --- real-time processing --- space-borne SAR --- deceptive jamming --- Doppler sensor --- acoustic vector sensor --- road traffic monitoring --- water column image --- gas emissions --- automatic detection --- optical flow --- parallax --- cloud --- earth observation --- geostationary satellite --- meteorological radar --- MSG --- SEVIRI --- sonar --- data fusion --- sensor design --- target tracking --- target imaging --- image understanding --- target recognition