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Remote Sensing Data Fusion
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Topic review
Updated time: 30 Oct 2020
Submitted by: Ciril Bohak
Definition: Direct point-cloud visualisation is a common approach for visualising large datasets of aerial terrain LiDAR scans. However, because of the limitations of the acquisition technique, such visualisations often lack the desired visual appeal and quality, mostly because certain types of objects are incomplete or entirely missing (e.g., missing water surfaces, missing building walls and missing parts of the terrain). To improve the quality of direct LiDAR point-cloud rendering, we present a point-cloud processing pipeline that uses data fusion to augment the data with additional points on water surfaces, building walls and terrain through the use of vector maps of water surfaces and building outlines. In the last step of the pipeline, we also add colour information, and calculate point normals for illumination of individual points to make the final visualisation more visually appealing. We evaluate our approach on several parts of the Slovenian LiDAR dataset.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 06 Apr 2021
Submitted by: Carson Leung
Definition: In recent years, artificial intelligence (AI) and its subarea of deep learning have drawn the attention of many researchers. At the same time, advances in technologies enable the generation or collection of large amounts of valuable data (e.g., sensor data) from various sources in different applications, such as those for the Internet of Things (IoT), which in turn aims towards the development of smart cities. With the availability of sensor data from various sources, sensor information fusion is in demand for effective integration of big data.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 17 Feb 2021
Submitted by: Mahdi Rezaei
Definition: An Autonomous Vehicle (AV), or a driverless car, or a self-driving vehicle is a car, bus, truck, or any other vehicle that is able to drive from point A to point B and perform all necessary driving operations and functions without any human intervention. An Autonomous Vehicle is normally equipped with different types of sensors to perceive the surrounding environment, including Normal Vision Cameras, Infrared Cameras, RADAR, LiDAR, and Ultrasonic Sensors. An autonomous vehicle should be able to detect and recognise all type of road users including surrounding vehicles, pedestrians, cyclists, traffic signs, road markings, and can segment the free spaces, intersections, buildings, and trees to perform a safe driving task. Currently, no realistic prediction expects we see fully autonomous vehicles earlier than 2030.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 11 Feb 2021
Submitted by: Mahdi Rezaei
Definition: An Autonomous Vehicle (AV), or a driverless car, or a self-driving vehicle is a car, bus, truck, or any other vehicle that is able to drive from point A to point B and perform all necessary driving functions, without any human intervention. An Autonomous Vehicle is normally equipped with different types of sensors to perceive the surrounding environment, including Normal Vision Cameras, Infrared Cameras, RADAR, LiDAR, and Ultrasonic Sensors. An autonomous vehicle should be able to detect and recognise all type of road users including surrounding vehicles, pedestrians, cyclists, traffic signs, road markings, and can segment the free spaces, intersections, buildings, and trees to perform a safe driving task. Currently, no realistic prediction expects we see fully autonomous vehicles earlier than 2030.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 28 Oct 2020
Submitted by: Michał Meina
Definition: Chronic stress is the main cause of health problems in high-risk jobs. Wearable sensors can become an ecologically valid method of stress level assessment in real-life applications. We sought to determine a non-invasive technique for objective stress monitoring. Data were collected from firefighters during 24-h shifts using sensor belts equipped with a dry-lead electrocardiograph (ECG) and a three-axial accelerometer. Levels of stress experienced during fire incidents were evaluated via a brief self-assessment questionnaire. Types of physical activity were distinguished basing on accelerometer readings, and heart rate variability (HRV) time series were segmented accordingly into corresponding fragments. Those segments were classified as stress/no-stress conditions. Receiver Operating Characteristic (ROC) analysis showed true positive classification as stress condition for 15% of incidents (while maintaining almost zero False Positive Rate), which parallels the amount of truly stressful incidents reported in the questionnaires. These results show a firm correspondence between the perceived stress level and physiological data. Psychophysiological measurements are reliable indicators of stress even in ecological settings and appear promising for chronic stress monitoring in high-risk jobs, such as firefighting.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 28 Oct 2020
Submitted by: Yuichi Sei
Definition: Crowd sensing (also known as participatory sensing, or mobile crowdsensing) is a means of collecting people’s surrounding information via mobile sensing devices.Its highly expressive and powerful sensing capabilitiescan carry out a big sensing project byfragmenting tasks into small pieces.The key to success is to get more participants to collect higher quality data.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 29 Oct 2020
Submitted by: Svilen Sabchevski
Definition: Gyrotrons are among the most powerful sources of coherent radiation that operate in CW and long pulse regimes in the sub-THz and the THz frequency ranges of the electromagnetic spectrum, i.e. between 0.3 THz and 3.0 THz (corresponding to wavelengths from 1.0 to 0.1 mm). This region, which spans between the frequency bands occupied by various electronic and photonic devices, respectively, is habitually called a THz power gap. The underlying mechanism of the operation of the gyrotron involves a formation of bunches of electrons gyrating in a helical electron beam and their synchronous interaction with a fast (i.e. having a superluminal phase velocity) electromagnetic wave, producing a bremsstrahlung radiation. In contrast to the slow-wave tubes, which utilize tiny structures with dimensions comparable to the wavelength of the radiation, the gyrotrons have a simpler resonant system (cavity resonator) with dimensions that are much greater than the wavelength. This allows much more powerful electron beams to be used and thus higher output powers to be achieved. Although in comparison with the classical microwave tubes the gyrotrons are characterized by greater volume and weight due to the presence of bulky parts (such as superconducting magnets and massive collectors where the energy of the spent electron beam is dissipated) they are much more compact and can easily be embedded in a sophisticated laboratory equipment (e.g. spectrometers, technological systems, etc.) than other devices such as free-electron lasers (FEL) and radiation sources based on electron accelerators. Nowadays, the gyrotrons are used as powerful sources of coherent radiation in the wide fields of high-power sub-THz and THz science and technologies [1][2][3].
Entry Collection : Remote Sensing Data Fusion
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Biography
Updated time: 29 Dec 2020
Submitted by: Han-Chuan Hsieh
Abstract: Han-Chuan Hsieh was received a B.S. degree in Electrical Engineering from National Taipei University of Technology (NTUT), in 1998, and an M.S. degree in Communication Engineering from Tatung Institute of Technology, Taipei, Taiwan, in 2008. He has been a Ph.D. degree in Department of Electrical Engineering of National Taiwan University of Science and Technology (NTUST).
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 22 Feb 2021
Submitted by: Nanchao Wang
Definition: High-spectral-resolution lidar (HSRL) is a powerful tool for atmospheric aerosol remote sensing. A ground-based high-spectral-resolution lidar (HSRL), operated at 532 nm wavelength, has been developed at Zhejiang University (ZJU) for aerosols and clouds studies. This lidar provides vertical profiles of aerosol scattering ratio together with lidar ratio and particle depolarization ratio at 532 nm. Determination of overlap function is a key step in the calibration of a high-spectral-resolution lidar (HSRL) and important guarantee of data retrieval, an iterative-based general determination (IGD) method for overlap function in HSRL is proposed. The standard method to retrieve the extinction coefficient from HSRL signals depends heavily on the signal-to-noise ratio (SNR). An iterative image reconstruction (IIR) method is proposed for the retrieval of the aerosol extinction coefficient based on HSRL data under low SNR condition. With the optical properties, a state-of-the-art method for feature detection and classification is proposed to automatically identify the features attributed to dust/polluted dust, urban/smoke, maritime aerosols, as well as ice and liquid water cloud during day and night.
Entry Collection : Remote Sensing Data Fusion
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Topic review
Updated time: 13 Apr 2021
Submitted by: Thanos Stavropoulos
Definition: Interconnected sensing technology, such as IoT wearables and devices, present a promising solution for objective, reliable, and remote monitoring, assessment, and support through ambient assisted living.
Entry Collection : Remote Sensing Data Fusion
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