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A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images

Stelios Mylonas, Dimitris Stavrakoudis, John Theocharis, Paris Mastorocostas
2015 Remote Sensing  
This paper proposes an object-based segmentation/classification scheme for remotely sensed images, based on a novel variant of the recently proposed Genetic Sequential Image Segmentation (GeneSIS) algorithm  ...  Furthermore, the suggested methods achieve higher classification accuracies and good segmentation maps compared to a series of existing algorithms.  ...  Conflicts of Interest The authors declare no conflict of interest. Remote Sens. 2015, 7  ... 
doi:10.3390/rs70302474 fatcat:ljkla6yg7ventgyl67wechdfi4

GEOSPATIAL DATA PROCESSING CHARACTERISTICS FOR ENVIRONMENTAL MONITORING TASKS

Olga BUTENKO, Stanislav HORELIK, Oleh ZYNYUK
2020 Architecture Civil Engineering Environment  
It is determined that the use of image segmentation algorithms based on minimizing or maximizing the selected criterion for clustering quality, for example, algorithms that use kmeans and dynamic condensation  ...  However, the developers of these techniques emphasize that the presence of a number of interactive processes, such as contouring, searching for reference information, classification of images by texture  ... 
doi:10.21307/acee-2020-008 fatcat:kguczj2forft5fpivn6lujbsna

Distributed Deep Learning for Remote Sensing Data Interpretation

J. M. Haut, M. E. Paoletti, S. Moreno, J. Plaza, J. A. Rico, A. Plaza
2022 Zenodo  
In this paper, we provide a comprehensive review of the state-of-the-art in deep learning for remote sensing data interpretation, analyzing the strengths and weaknesses of the most widely used techniques  ...  Nowadays, technological advances in terms of software and hardware have a noticeable impact on Earth observation applications, more specifically in remote sensing techniques and procedures, allowing for  ...  The paper [100] proposes a highly scalable and efficient segmentation model for remotely sensed images, capable of segmenting very high resolution imagery with DL algorithms.  ... 
doi:10.5281/zenodo.6413870 fatcat:c5hea52k2jfebjshcozf5dww7q

A Method for Post-hazard Assessment Through Topography Analysis using Regional Segmentation for Multi-temporal Satellite Imagery: A Case Study of 2011 Tohuku Earthquake Region

Pushan Kumar Dutta, O.P. Mishra, M.K. Naskar
2013 International Journal of Image Graphics and Signal Processing  
Based on the satellite image analysis through image segmentation, it is found that the area of .997 km 2 for the Honshu region was a maximu m damage zone localized in the coastal belt of NE Japan fore-arc  ...  In fact, image segmentation using graph cut can be understood as the process of assigning a label to every pixel in an image, the same Segmentation for Multi-temporal Satellite Imagery : A Case Study of  ...  The utilities of such studies in satellite image analysis involves remote sensing (mu ltispectral classification) [7] ,environ mental mon itoring, change detection [8] and weather forecasting.  ... 
doi:10.5815/ijigsp.2013.10.08 fatcat:jw7zhrzrbbgljh4x3epes5avn4

The use of remote sensing in soil and terrain mapping — A review

V.L. Mulder, S. de Bruin, M.E. Schaepman, T.R. Mayr
2011 Geoderma  
But, in areas with exhaustive lichen cover, the overall lower reflectance has to be accounted for. We are not aware of any remote sensing based lichen mapping study on a plot or local scale.  ...  over parametric classification algorithms.  ... 
doi:10.1016/j.geoderma.2010.12.018 fatcat:dp3fpbppera4hkviorqwzsymn4

Remote Sensed Image Processing on Grids for Training in Earth Observation [chapter]

Dana Petcu, Daniela Zaharie, Marian Neagul, Silviu Panica, Marc Frincu, Dorian Gorgan, Teodor Stefanut, Victor Bacu
2009 Image Processing  
In this context, the chapter presents for the beginners an overview of the technological challenges and user requirements in remote sensed image processing, as well as the solutions provided by the Grid-based  ...  Remote sensing systems integrate cameras, scanners, radiometers, radar and other devices, and deal with the collection, processing, and distribution of large amounts of data.  ...  Grid computing for remote sensed image processing Remote sensing is a major technological and scientific tool for monitoring planetary surfaces and atmospheres.  ... 
doi:10.5772/7049 fatcat:clowq2cwsved3bu4guvxwyg26a

The New Approach of Using Image and Range Based Methods for Quality Control of Dimension Stone

Volodymyr Levytskyi
2017 Reports on Geodesy and Geoinformatics  
This paper describes a new approach of fracturing identification, based on image and range data, which realized by image processing and special software.  ...  In this article describes a method using new computer algorithms that allow for automated identification and calculation of fracturing parameters.  ...  Acknowledgements This work was supported by the Department of Photogrammetry, Remote Sensing and Geographic Information Systems of Warsaw University of Technology under the project Erasmus Mundus Action  ... 
doi:10.1515/rgg-2017-0006 fatcat:r2wtc2ve3zd6zln36g7vsijyce

Semantic segmentation on small datasets of satellite images using convolutional neural networks

Mohammed Chachan Younis, Edward Keedwell
2019 Journal of Applied Remote Sensing  
Semantic segmentation is one of the most popular and challenging applications of deep learning.  ...  A SegNet-based neural network with an encoder-decoder architecture is employed. Despite the small size of the dataset, the results are promising.  ...  In Ref. 33 , segmentation on nine categories from remotely sensed images using genetic sequential image segmentation, an iterative segmentation algorithm, tries to optimize the local balance between coverage  ... 
doi:10.1117/1.jrs.13.046510 fatcat:cz7rimaaebgnjfzegqkpmbfene

Gradient-based edge detection and feature classification of sea-surface images of the Southern California Bight

John J. Oram, James C. McWilliams, Keith D. Stolzenbach
2008 Remote Sensing of Environment  
An edge detection algorithm was developed that is capable of objectively detecting significant edges in remotely sensed images of the surface ocean.  ...  The algorithm utilizes a gradient-based edge detector that is less sensitive to noise in the input image than previously used detectors and has the ability to detect edges at different length scales.  ...  Summary The edge detection algorithm developed here is able to objectively detect significant edges in remotely sensed images of the surface ocean.  ... 
doi:10.1016/j.rse.2007.11.010 fatcat:6ojzs5fm35fjhbv6yghet5lxpy

Detection of buildings in spaceborne TomoSAR point clouds via hybrid region growing and energy minimization technique

Muhammad Shahzad, Xiao Xiang Zhu
2015 2015 Joint Urban Remote Sensing Event (JURSE)  
The presented approach is illustrated and validated by examples using TomoSAR point clouds generated from a stack of TerraSAR-X high resolution spotlight images covering an area of approximately 1.5 km  ...  The approach is systematic and allows robust detection of both tall and low height buildings and is, therefore, well suited for urban monitoring of larger areas from space.  ...  The idea is to search in the nearby vicinity of the reconstructed façade to select seed points and then employ a surface normals based region growing algorithm to extract existing roof points.  ... 
doi:10.1109/jurse.2015.7120480 dblp:conf/jurse/ShahzadZ15 fatcat:sglfofgh7fbthg5blnagrwfbv4

QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS

S. Sen, N. Turel
2020 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
We also provide a theoretical framework for quantification of such uncertainty and argue that the standards of accuracy of such data should account for errors and omissions during auto segmentation and  ...  We review different sources of uncertainty introduced by ML based classification and segmentation and outline concepts of uncertainty that is inherent in such automatically processed data.  ...  ACKNOWLEDGEMENTS We acknowledge the support of Genesys International and colleagues for the use case and data related to the power utility example.  ... 
doi:10.5194/isprs-archives-xliv-m-2-2020-87-2020 fatcat:a2ijofftfbf6dlwqnv43o2g4om

Novel approach to enhance coastal habitat and biotope mapping with drone aerial imagery analysis

João Gama Monteiro, Jesús L. Jiménez, Francesca Gizzi, Petr Přikryl, Jonathan S. Lefcheck, Ricardo S. Santos, João Canning-Clode
2021 Scientific Reports  
Finally, we propose a general workflow that can be adapted to different needs and aerial platforms, which can be used as blueprints for further integration of remote-sensing with in situ surveys to produce  ...  the ecological consequences of natural and anthropogenic impacts.  ...  Second, satellites obtain a fixed set of images every day regardless of the local conditions.  ... 
doi:10.1038/s41598-020-80612-7 pmid:33436894 fatcat:nsppr7t325auldkp66jjdwjap4

Fusing Meter-Resolution 4-D InSAR Point Clouds and Optical Images for Semantic Urban Infrastructure Monitoring

Yuanyuan Wang, Xiao Xiang Zhu, Bernhard Zeisl, Marc Pollefeys
2017 IEEE Transactions on Geoscience and Remote Sensing  
in remote sensing.  ...  This paper presents a framework of a semantic-level deformation monitoring by linking the precise deformation estimates of SAR interferometry and the semantic classification labels of optical images via  ...  ACKNOWLEDGMENT The authors would like to thank Dr. H. Hirschmüller of DLR-RM for providing the optical data of 7-cm resolution as well as the reviewers for their valuable suggestions.  ... 
doi:10.1109/tgrs.2016.2554563 fatcat:2vjfxv25tjf5leasrb6scbapjm

Applications and Challenges of Artificial Intelligence in Space Missions

Paul A. Oche, Gideon A. Ewa, Nwanneka Ibekwe
2021 IEEE Access  
These limitations have necessitated the need to have a concise survey with a wider scope for those interested in the applications and challenges of AI in the space industry, especially those with technical  ...  The first category suffers from the limitation of being old and not covering some crucial and recent developments in the field; such as the contributions of Deep Learning (DL) and bioinspired AI algorithms  ...  [168] performed the combination of both supervised and unsupervised modes of change detection and on a pixel-based method to achieve better classification of remote sensing images.  ... 
doi:10.1109/access.2021.3132500 fatcat:2n5el5dcqzgdtc3brca5xwxrfu

MOTION COMPONENT SUPPORTED BOOSTED CLASSIFIER FOR CAR DETECTION IN AERIAL IMAGERY

S. Tuermer, J. Leitloff, P. Reinartz, U. Stilla
2013 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
Research of automatic vehicle detection in aerial images has been done with a lot of innovation and constantly rising success for years. However information was mostly taken from a single image only.  ...  On closer viewing the moving objects are mainly vehicles and therefore we provide a method which is able to limit the search space of the detector to changed areas.  ...  To give an impression how helpful the motion mask is, we display the result of a classification without motion mask in Fig. 6 . The next images show the genesis of the motion mask.  ... 
doi:10.5194/isprsarchives-xxxviii-3-w22-215-2011 fatcat:6ge77lbj55abni5anzxh6juzfm
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