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A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images
2015
Remote Sensing
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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 ...
GeneSIS segments the image in an iterative manner, whereby at each iteration a single object is extracted via a genetic-based object extraction algorithm. ...
Conflicts of Interest The authors declare no conflict of interest. Remote Sens. 2015, 7 ...
doi:10.3390/rs70302474
fatcat:ljkla6yg7ventgyl67wechdfi4
Wetland Mapping of Sundar Ban Delta Using Automatic Feature Extraction
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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The automatic extraction of objects from data and images has been a topic of research for decades. ...
Based on the radiometric and geometric behaviours of feature, the snake model is modified in two areas: the criteria for the selection of initial seeds and the external energy function. ...
Rawat, Head of Geography, SSJ Campus Almora, and Dr. Pankaj Kumar Bhatt, LSM GPG College, Pithoragarh, Kumaun University, Nainital for provide the facility. And we also thank to Mr. ...
doi:10.23956/ijarcsse/v7i6/0263
fatcat:6ch2hia6fzdu3kzmcmlqplwnf4
Identification of Hydrothermal Alteration Minerals for Exploring Gold Deposits Based on SVM and PCA Using ASTER Data: A Case Study of Gulong
2019
Remote Sensing
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In this paper, remote sensing methods are used to circle the favorable metallogenic areas and find new ore points for Gulong. ...
The results show that the mineral alteration extraction method proposed in this paper has certain guiding significance for metallogenic prediction by remote sensing. ...
Remote sensing image classification based on the optimal support
the angle between the hyperplane unit normal and the multi-band remote sensing images, the first problem needs to be solved is how to ...
doi:10.3390/rs11243003
fatcat:25aj4ocmpbesjavjtxd3wqxsse
2015 Index IEEE Transactions on Geoscience and Remote Sensing Vol. 53
2015
IEEE Transactions on Geoscience and Remote Sensing
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Marsetic, A., +, TGRS Nov. 2015 6035-6047 Classification of Remotely Sensed Images Using the GeneSIS Fuzzy Segmentation Algorithm. ...
., +, TGRS May 2015 2683-2695 Classification of Remotely Sensed Images Using the GeneSIS Fuzzy Segmentation Algorithm. ...
Radiofrequency interference A Methodology to Determine Radio-Frequency Interference in AMSR2 Observations. ...
doi:10.1109/tgrs.2015.2513444
fatcat:zuklkpk4gjdxjegoym5oagotzq
Extraction of Buildings in VHR SAR Images Using Fully Convolution Neural Networks
2018
IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium
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AUTOMATIC ANNOTATION OF SAR IMAGES Annotating an image is fundamental for application of any supervised learning technique for segmentation/ classification purposes. ...
As we are using a FCN we exploit the ability to not only classify a single pixel as proposed in [5] [14] [4] but we perform image segmentation for input images of arbitrary size at once. ...
doi:10.1109/igarss.2018.8519603
dblp:conf/igarss/ShahzadMFWZ18
fatcat:6cx6qjkwbff6hnehj4q36lskfu
Remote Sensing for Mapping and Monitoring Wetlands and Small Lakes in Southeast Brazil
[chapter]
2012
Remote Sensing of Planet Earth
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The authors are thankful to the Forestry Institute of Minas Gerais (IEF-MG) for providing the Ikonos and RapidEye data and field support. ...
We are most thankful to Thaís Amaral Moreira for her hard work in mapping and statistics. ...
Because MAGIC associates the segments to a predefined set of classes, it is considered a region-based unsupervised classification system. ...
doi:10.5772/32414
fatcat:arqsrubqxveebcyl4ewdk6pnqi
A location-based approach to the classification of mesoscale oceanic structures in SeaWiFS and Aqua-MODIS images of Northwest Africa
2015
International Journal of Remote Sensing
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This study presents a different approach to the classification of Mesoscale Oceanic Structures (MOS) present in the Northwest African area, based on their location. ...
To identify and label the MOS classified in the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Aqua-MODIS (Moderate Resolution Imaging Spectroradiometer) chlorophyll-a and temperature images, we used ...
Thresholding returns a binary image of the region to be segmented. ...
doi:10.1080/01431161.2015.1111540
fatcat:twevwqga55g4ff5etgag6cqzfe
Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks
2016
Remote Sensing
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The results of the full classification and segmentation on selected segments of the map show that CNNs are a viable tool for solving both the segmentation and object recognition task for remote sensing ...
The availability of high-resolution remote sensing (HRRS) data has opened up the possibility for new interesting applications, such as per-pixel classification of individual objects in greater detail. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/rs8040329
fatcat:6vmtregvcraslkp2fj7562tdja
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
2013
International Journal of Image Graphics and Signal Processing
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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 ...
Efficiency of graph cut with α expansions for remote sensing applications Energy minimization is a mu ltilevel algorith m( background ar object of interest) so graph cut algorithm alone takes more t ime ...
doi:10.5815/ijigsp.2013.10.08
fatcat:jw7zhrzrbbgljh4x3epes5avn4
SEMANTIC INTERPRETATION OF INSAR ESTIMATES USING OPTICAL IMAGES WITH APPLICATION TO URBAN INFRASTRUCTURE MONITORING
2015
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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However, the current deformation analysis still remains at a primitive stage of pixel-wise motion parameter inversion and manual identification of the regions of interest. ...
Since the launch of meter-resolution spaceborne SAR sensors, the InSAR community has shown that even individual buildings can be monitored in high level of detail. ...
It lacks a systematic way to monitor the region of interest, for example, the railway or the road network in a city. ...
doi:10.5194/isprsarchives-xl-3-w3-153-2015
fatcat:3ah2hkaztbg4pgt4uzagjanmgy
Buildings Detection in VHR SAR Images Using Fully Convolution Neural Networks
2019
IEEE Transactions on Geoscience and Remote Sensing
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2018 pre-print arXiv:1808.06155v1 fatcat:z75ml7hgwndshm7ha3xjkc27ra
Such a cascaded formation has been successfully employed in computer vision and remote sensing fields for optical image classification but, to our knowledge, has not been applied to SAR images. ...
represented as a Recurrent Neural Network to detect building regions in a single VHR SAR image. ...
This ability of Neural Networks motivated us to use a semantic segmentation network from Computer Vision as base for our SAR Image Classification Network. ...
doi:10.1109/tgrs.2018.2864716
fatcat:47lodcuvbbclroo2sykc2xctaq
Gradient-based edge detection and feature classification of sea-surface images of the Southern California Bight
2008
Remote Sensing of Environment
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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
Spectral Analysis of Water Reflectance for Hyperspectral Remote Sensing of Water Quailty in Estuarine Water
2014
Journal of Geoscience and Environment Protection
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The prime objective of this study was to develop algorithms for hyperspectral remote sensing of water quality based on in situ spectral measurement of water reflectance. ...
However, the optical complexity of case 2 water makes the water quality monitoring by remote sensing in estuarine water a challenge. ...
This work was partly supported by NOAA ECSC program, the NSF award 1036586 to university of Maryland Eastern Shore, and the USDA NIFA award VAE-2011-02523 to Virginia State University (sub-award to Morgan ...
doi:10.4236/gep.2014.22004
fatcat:k473bv3265gfvgtxsmmiuyngda
Surface Water Change Detection via Water Indices and Predictive Modeling Using Remote Sensing Imagery: A Case Study of Nuntasi-Tuzla Lake, Romania
2022
Water
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The experimental results indicate that the proposed classification methods can extract relevant features from waterbodies using remote sensing imagery with a high accuracy. ...
Water body feature extraction using a remote sensing technique represents an important tool in the investigation of water resources and hydrological drought assessment. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/w14040556
fatcat:s4b6oep6ondjlolmihtpd3hmhi
The use of remote sensing in soil and terrain mapping — A review
2011
Geoderma
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over parametric classification algorithms. ...
Considering the use of remote sensing for regional digital soil mapping, research is needed on extending current methods beyond the plot. ...
doi:10.1016/j.geoderma.2010.12.018
fatcat:dp3fpbppera4hkviorqwzsymn4
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