scholarly journals Change Detection Based on Artificial Intelligence: State-of-the-Art and Challenges

2020 ◽  
Vol 12 (10) ◽  
pp. 1688 ◽  
Author(s):  
Wenzhong Shi ◽  
Min Zhang ◽  
Rui Zhang ◽  
Shanxiong Chen ◽  
Zhao Zhan
Keyword(s):  
Artificial Intelligence ◽  
Change Detection ◽  
State Of The Art ◽  
Implementation Process ◽  
Heterogeneous Data ◽  
Point Of View ◽  
Detection Methods ◽  
Wide Range ◽  
Disaster Assessment ◽  
Open Datasets

Change detection based on remote sensing (RS) data is an important method of detecting changes on the Earth’s surface and has a wide range of applications in urban planning, environmental monitoring, agriculture investigation, disaster assessment, and map revision. In recent years, integrated artificial intelligence (AI) technology has become a research focus in developing new change detection methods. Although some researchers claim that AI-based change detection approaches outperform traditional change detection approaches, it is not immediately obvious how and to what extent AI can improve the performance of change detection. This review focuses on the state-of-the-art methods, applications, and challenges of AI for change detection. Specifically, the implementation process of AI-based change detection is first introduced. Then, the data from different sensors used for change detection, including optical RS data, synthetic aperture radar (SAR) data, street view images, and combined heterogeneous data, are presented, and the available open datasets are also listed. The general frameworks of AI-based change detection methods are reviewed and analyzed systematically, and the unsupervised schemes used in AI-based change detection are further analyzed. Subsequently, the commonly used networks in AI for change detection are described. From a practical point of view, the application domains of AI-based change detection methods are classified based on their applicability. Finally, the major challenges and prospects of AI for change detection are discussed and delineated, including (a) heterogeneous big data processing, (b) unsupervised AI, and (c) the reliability of AI. This review will be beneficial for researchers in understanding this field.

scholarly journals Development of Knowledge Graph for Data Management Related to Flooding Disasters Using Open Data

2021 ◽  
Vol 13 (5) ◽  
pp. 124
Author(s):  
Jiseong Son ◽  
Chul-Su Lim ◽  
Hyoung-Seop Shim ◽  
Ji-Sun Kang
Keyword(s):  
Artificial Intelligence ◽  
Domain Knowledge ◽  
Open Data ◽  
Heterogeneous Data ◽  
Big Data Analysis ◽  
Knowledge Graph ◽  
Cross Domain ◽  
Disaster Data ◽  
Knowledge Graphs ◽  
Open Datasets

Despite the development of various technologies and systems using artificial intelligence (AI) to solve problems related to disasters, difficult challenges are still being encountered. Data are the foundation to solving diverse disaster problems using AI, big data analysis, and so on. Therefore, we must focus on these various data. Disaster data depend on the domain by disaster type and include heterogeneous data and lack interoperability. In particular, in the case of open data related to disasters, there are several issues, where the source and format of data are different because various data are collected by different organizations. Moreover, the vocabularies used for each domain are inconsistent. This study proposes a knowledge graph to resolve the heterogeneity among various disaster data and provide interoperability among domains. Among disaster domains, we describe the knowledge graph for flooding disasters using Korean open datasets and cross-domain knowledge graphs. Furthermore, the proposed knowledge graph is used to assist, solve, and manage disaster problems.

scholarly journals Evaluation of Unsupervised Change Detection Methods Applied to Landslide Inventory Mapping Using ASTER Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1987 ◽  
Author(s):  
Rocío Ramos-Bernal ◽  
René Vázquez-Jiménez ◽  
Raúl Romero-Calcerrada ◽  
Patricia Arrogante-Funes ◽  
Carlos Novillo
Keyword(s):  
Change Detection ◽  
Vegetation Index ◽  
Thermal Emission ◽  
Principal Component ◽  
Detection Methods ◽  
Detection Accuracy ◽  
Data Types ◽  
Statistical Parameters ◽  
Wide Range ◽  
The World

Natural hazards include a wide range of high-impact phenomena that affect socioeconomic and natural systems. Landslides are a natural hazard whose destructive power has caused a significant number of victims and substantial damage around the world. Remote sensing provides many data types and techniques that can be applied to monitor their effects through landslides inventory maps. Three unsupervised change detection methods were applied to the Advanced Spaceborne Thermal Emission and Reflection Radiometer (Aster)-derived images from an area prone to landslides in the south of Mexico. Linear Regression (LR), Chi-Square Transformation, and Change Vector Analysis were applied to the principal component and the Normalized Difference Vegetation Index (NDVI) data to obtain the difference image of change. The thresholding was performed on the change histogram using two approaches: the statistical parameters and the secant method. According to previous works, a slope mask was used to classify the pixels as landslide/No-landslide; a cloud mask was used to eliminate false positives; and finally, those landslides less than 450 m2 (two Aster pixels) were discriminated. To assess the landslide detection accuracy, 617 polygons (35,017 pixels) were sampled, classified as real landslide/No-landslide, and defined as ground-truth according to the interpretation of color aerial photo slides to obtain omission/commission errors and Kappa coefficient of agreement. The results showed that the LR using NDVI data performs the best results in landslide detection. Change detection is a suitable technique that can be applied for the landslides mapping and we think that it can be replicated in other parts of the world with results similar to those obtained in the present work.

scholarly journals An object-based approach for semi-automated landslide change detection and attribution of changes to landslide classes in northern Taiwan

2015 ◽  
Vol 8 (2) ◽  
pp. 327-335 ◽  
Author(s):  
Daniel Hölbling ◽  
Barbara Friedl ◽  
Clemens Eisank
Keyword(s):  
Change Detection ◽  
Spatial Resolution ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Detection Methods ◽  
Detection And Attribution ◽  
Object Based ◽  
Wide Range ◽  
Northern Taiwan

Abstract Earth observation (EO) data are very useful for the detection of landslides after triggering events, especially if they occur in remote and hardly accessible terrain. To fully exploit the potential of the wide range of existing remote sensing data, innovative and reliable landslide (change) detection methods are needed. Recently, object-based image analysis (OBIA) has been employed for EO-based landslide (change) mapping. The proposed object-based approach has been tested for a sub-area of the Baichi catchment in northern Taiwan. The focus is on the mapping of landslides and debris flows/sediment transport areas caused by the Typhoons Aere in 2004 and Matsa in 2005. For both events, pre- and post-disaster optical satellite images (SPOT-5 with 2.5 m spatial resolution) were analysed. A Digital Elevation Model (DEM) with 5 m spatial resolution and its derived products, i.e., slope and curvature, were additionally integrated in the analysis to support the semi-automated object-based landslide mapping. Changes were identified by comparing the normalised values of the Normalized Difference Vegetation Index (NDVI) and the Green Normalized Difference Vegetation Index (GNDVI) of segmentation-derived image objects between pre- and post-event images and attributed to landslide classes.

Bodily Processing: What Progress Has Been Made in Understanding the Embodiment of Computing Systems?

2021 ◽  
Vol 66 (2 supplement) ◽  
pp. 181-190
Author(s):  
Martina Properzi
Keyword(s):  
Artificial Intelligence ◽  
Recent Trend ◽  
State Of The Art ◽  
Point Of View ◽  
Computing Systems ◽  
Disciplinary Field ◽  
Morphological Computation ◽  
Unconventional Computation ◽  
Artificial Intelli ◽  
Made In

" In this article I will address the issue of the embodiment of computing sys-tems from the point of view distinctive of the so-called Unconventional Computation, focusing on the paradigm known as Mor-phological Computation. As a first step, I will contextualize Morphological Computa-tion within the disciplinary field of Embod-ied Artificial Intelligence: broadly con-ceived, Embodied Artificial Intelligence may be characterized as embracing both conventional and unconventional ap-proaches to the artificial emulation of natu-ral intelligence. Morphological Computa-tion stands out from other paradigms of unconventional Embodied Artificial Intelli-gence in that it discloses a new, closer kind of connection between embodiment and computation. I will further my investigation by briefly reviewing the state-of-the-art in Morphological Computation: attention will be given to a very recent trend, whose core concept is that of “organic reconfigu-rability”. In this direction, as a final step, two advanced cases of study of organic or living morphological computers will be pre-sented and discussed. The prospect is to shed some light on our title question: what progress has been made in understanding the embodiment of computing systems? Keywords: Embodied Artificial Intelligence; Morphological Computation; Reservoir Compu-ting Systems; Organic Reconfigurability; 3D Bio-Printed Synthetic Corneas; Xenobots "

scholarly journals Robotics and Artificial Intelligence in Gastrointestinal Endoscopy: Updated Review of the Literature and State of the Art

2021 ◽  
Author(s):  
Ivo Boškoski ◽  
Beatrice Orlandini ◽  
Luigi Giovanni Papparella ◽  
Maria Valeria Matteo ◽  
Martina De Siena ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Gastrointestinal Endoscopy ◽  
State Of The Art ◽  
Unmet Need ◽  
Diagnostic Techniques ◽  
Review Of The Literature ◽  
The Past ◽  
Wide Range ◽  
Near Future ◽  
Artificial Intelligence Systems

Abstract Purpose of Review Gastrointestinal endoscopy includes a wide range of procedures that has dramatically evolved over the past decades. Robotic endoscopy and artificial intelligence are expanding the horizons of traditional techniques and will play a key role in clinical practice in the near future. Understanding the main available devices and procedures is a key unmet need. This review aims to assess the current and future applications of the most recently developed endoscopy robots. Recent Findings Even though a few devices have gained approval for clinical application, the majority of robotic and artificial intelligence systems are yet to become an integral part of the current endoscopic instrumentarium. Some of the innovative endoscopic devices and artificial intelligence systems are dedicated to complex procedures such as endoscopic submucosal dissection, whereas others aim to improve diagnostic techniques such as colonoscopy. Summary A review on flexible endoscopic robotics and artificial intelligence systems is presented here, showing the m3ost recently approved and experimental devices and artificial intelligence systems for diagnosis and robotic endoscopy.

scholarly journals Change Detection for Heterogeneous Remote Sensing Images with Improved Training of Hierarchical Extreme Learning Machine (HELM)

2021 ◽  
Vol 13 (23) ◽  
pp. 4918
Author(s):  
Te Han ◽  
Yuqi Tang ◽  
Xin Yang ◽  
Zefeng Lin ◽  
Bin Zou ◽  
...  
Keyword(s):  
Change Detection ◽  
Extreme Learning Machine ◽  
State Of The Art ◽  
Sample Selection ◽  
Training Sample ◽  
Google Earth ◽  
Detection Methods ◽  
Feature Maps ◽  
Optical Images ◽  
Learning Machine

To solve the problems of susceptibility to image noise, subjectivity of training sample selection, and inefficiency of state-of-the-art change detection methods with heterogeneous images, this study proposes a post-classification change detection method for heterogeneous images with improved training of hierarchical extreme learning machine (HELM). After smoothing the images to suppress noise, a sample selection method is defined to train the HELM for each image, in which the feature extraction is respectively implemented for heterogeneous images and the parameters need not be fine-tuned. Then, the multi-temporal feature maps extracted from the trained HELM are segmented to obtain classification maps and then compared to generate a change map with changed types. The proposed method is validated experimentally by using one set of synthetic aperture radar (SAR) images obtained from Sentinel-1, one set of optical images acquired from Google Earth, and two sets of heterogeneous SAR and optical images. The results show that compared to state-of-the-art change detection methods, the proposed method can improve the accuracy of change detection by more than 8% in terms of the kappa coefficient and greatly reduce run time regardless of the type of images used. Such enhancement reflects the robustness and superiority of the proposed method.

scholarly journals COMPARATIVE CHARACTERISTICS OF THE REGIONAL DEVELOPMENT OF INCLUSIVE TOURISM IN THE BLACK SEA REGION AND SPANISH CATALONIA

2021 ◽  
Author(s):  
Natalia Bielousova
Keyword(s):  
Black Sea ◽  
Leisure Activities ◽  
Implementation Process ◽  
People With Disabilities ◽  
Point Of View ◽  
Transport Infrastructure ◽  
The Black Sea ◽  
Black Sea Region ◽  
European Experience ◽  
Wide Range

The article reveals the essence of inclusive tourism as a new direction of the tourism sector, for the introduction of which in the regions of Ukraine, it is necessary to thoroughly study the world experience, compare the real possibilities of the natural resource and tourist and recreational potential, as well as the level of development of the sectoral infrastructure of the region, which is related to the implementation process. programs for the development of inclusive tourism. As an example of European experience in creating an inclusive environment, the region of Spanish Catalonia was considered, which has similar features to the Black Sea region of Ukraine: climatic and natural resources, the presence of a coastline with beaches for recreation and a variety of leisure activities, a wide range of tourist services and offers for all tourists , including for people with inclusion and people with disabilities. Provides a comprehensive description of the inclusive environment of the city of Barcelona - the center of Catalonia, which is considered the most suitable for tourists with inclusion (people with disabilities): transport infrastructure, information centers for the provision of various services and information, accessible Internet sites, availability of special transport, adapted hotel rooms and points food, availability of tourist locations, etc.). The attention is focused on Catalonia, as a region where there is already an established mechanism for providing tourist services to inclusive tourists, but as a rule to people with disabilities. Therefore, the question arises of involving all categories of inclusive tourists, including representatives of socially vulnerable segments of the population, including pensioners. This will make it possible to equalize the rights of all citizens to rest and receive social and cultural benefits. From the point of view of economic efficiency, the process of increasing the number of tourists will be natural. This step will expand the range of travel services, increase the number of jobs and solve the problem of socializing people with inclusion. The general characteristics of the resource and infrastructural component of the Black Sea region made it possible to assess the region's capabilities, identify problems and predict the strategy of introducing inclusive tourism in the future in this region of Ukraine.

Colorimetric research of self-luminous objects in software and hardware environments by the method of multidimensional scales implementation

2020 ◽  
pp. 43-50
Author(s):  
Yauheniya N. Saukova
Keyword(s):  
Metrological Traceability ◽  
Point Of View ◽  
Intermediate Precision ◽  
Technical Vision ◽  
Wide Range ◽  
Chromaticity Coordinates ◽  
Unity Of Measurements ◽  
Software And Hardware ◽  
Luminous Objects ◽  
Reference Samples

It is shown that the issues of metrological traceability for extended self-luminous objects with a wide range of brightness have not yet been resolved, since the rank scales of embedded systems are used for processing digital images. For such scales, there is no “fixed” unit, which does not allow you to get reliable results and ensure the unity of measurements. An experiment is described to evaluate the accuracy of determining the intensity (coordinates) of the color of self-luminous objects. In terms of repeatability and intermediate precision compared to the reference measurement method, the color and chromaticity coordinates of self-luminous objects (reference samples) were determined by their multiple digital registration using technical vision systems. The possibilities of the developed methodology for colorimetric studies in hardware and software environments from the point of view of constructing a multidimensional conditional scale are determined.

COMBINATORIAL POLYNOMIALLY COMPUTABLE CHARACTERISTICS OF SUBSTITUTIONS AND THEIR PROPERTIES

2020 ◽  
Vol 7 (2) ◽  
pp. 34-41
Author(s):  
VLADIMIR NIKONOV ◽  
◽  
ANTON ZOBOV ◽  
Keyword(s):  
Mathematical Expectation ◽  
Point Of View ◽  
Small Range ◽  
Computational Point ◽  
Wide Range ◽  
Bijective Function ◽  
The Difference ◽  
Element Base ◽  
Selection Of

The construction and selection of a suitable bijective function, that is, substitution, is now becoming an important applied task, particularly for building block encryption systems. Many articles have suggested using different approaches to determining the quality of substitution, but most of them are highly computationally complex. The solution of this problem will significantly expand the range of methods for constructing and analyzing scheme in information protection systems. The purpose of research is to find easily measurable characteristics of substitutions, allowing to evaluate their quality, and also measures of the proximity of a particular substitutions to a random one, or its distance from it. For this purpose, several characteristics were proposed in this work: difference and polynomial, and their mathematical expectation was found, as well as variance for the difference characteristic. This allows us to make a conclusion about its quality by comparing the result of calculating the characteristic for a particular substitution with the calculated mathematical expectation. From a computational point of view, the thesises of the article are of exceptional interest due to the simplicity of the algorithm for quantifying the quality of bijective function substitutions. By its nature, the operation of calculating the difference characteristic carries out a simple summation of integer terms in a fixed and small range. Such an operation, both in the modern and in the prospective element base, is embedded in the logic of a wide range of functional elements, especially when implementing computational actions in the optical range, or on other carriers related to the field of nanotechnology.

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