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http://www.asprs.org/a/publications/proceedings/pecora16/Pradhan_D.pdf
INTEGRATING SVM TOOLS IN ERDAS IMAGINE 8.7 FOR USDA’S CONSERVATION RESERVE PROGRAM MAPPING AND COMPLIANCE MONITORING ... [email protected] [email protected] ABSTRACT Our overall goal is to investigate the utility of Support Vector Machine (SVM) based semi-supervised classification ... SVM Tools into Erdas Imagine 8.7 to perform ...
https://www.hexagongeospatial.com/products/power-portfolio/erdas-imagine
Hexagon Geospatial ERDAS IMAGINE supplies tools for all remote sensing, photogrammetry, and GIS needs. Geospatial Division. ... Support Resources M.App Exchange ... Machine and Deep Learning algorithms that can be trained to automatically analyze massive amounts of data are improving geospatial workflows and advancing image processing.
https://community.hexagongeospatial.com/t5/IMAGINE-Discussions/ERDAS-IMAGINE-2018-Machine-Learning-Classification/m-p/23824
Hello, Is there anyone with an idea of how to refine the classification result from Machine Learning using ERDAS IMAGINE 2018? The attached screenshot is a result from raster classification using Machine Learning operators. The result doenst seem homogenoues or smooth/uniform. Same to the resu...
https://community.hexagongeospatial.com/t5/Spatial-Modeler-Tutorials/Machine-Learning-Example-Classifying-Features/ta-p/22616
There are two broad categories of Machine Learning classifiers introduced in ERDAS IMAGINE 2018. One deals with the broader category of Machine Learning which can be thought of as traditional classifiers (supervised or unsupervised) and includes Random …
https://www.hexagongeospatial.com/products/power-portfolio/erdas-imagine/erdas-imagine-product-release-details
ERDAS IMAGINE interface now runs natively in 64-bit, enabling embedded components such as the 2D View and Spatial Model Editor to leverage more of your available system memory and CPUs. Along with streamlined algorithms, this also provides more efficient execution of ERDAS IMAGINE in general. New operators enable machine-learning classification
https://imagemnl.com/wp-content/uploads/2018/08/ERDAS_IMAGINE_2018_Release_Guide.pdf
6. Live link connection between ERDAS IMAGINE and GeoMedia. If you routinely use any of these in your work then you might want to consider running ERDAS IMAGINE 2018 (32-bit) rather than ERDAS IMAGINE 2018 (64-bit). SUPPORT OF NEW FEATURE / VECTOR DATA FORMATS
https://en.wikipedia.org/wiki/ERDAS_Imagine
Hexagon AB is a global technology group headquartered in Sweden.. The operation is focused on precision measuring technologies and is divided into three business areas: Geospatial Measuring (Surveying and GPS), Industrial Metrology (Hexagon Metrology) and Technologies.The company markets its products and services under more than 35 different brands worldwide.Headquarters: Stockholm, Sweden
https://www.youtube.com/watch?v=i5pO5b-5iRc
Apr 25, 2017 · This video demonstrates how to perform image classification using Minimum Distance classifier in ERDAS Imagine. The minimum distance classifier (MDC) is an example of a commonly used ...Author: Anuj Tiwari
http://www.thaiscience.info/journals/Article/WJST/10958633.pdf
Land Use Classification using Support Vector Machine and Maximum Likelihood Algorithms by Landsat 5 TM Images . ... classification using a support vector machine (SVM) and maximum likelihood in classifier (MLC) ... images is performed using image to image methodthe by the …
https://www.loc.gov/preservation/digital/formats/fdd/fdd000420.shtml
Format Description for ERDAS_IMG -- A proprietary, partially documented format for multi-layer geo-referenced raster images developed originally for use with ERDAS IMAGINE software. A key capability of the format is that it distinguishes betweenthematic and continuous raster layers.
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