Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Effective utilization of bandwidth and storage space is important in imaging applications including remote sensing. Remote sensing applications use multi-sensory, multi-band, multi resolution images. Usually, remote sensing applications uses image classification results for their analysis and decision making. In this paper we propose a new JPEG based image compression algorithm based on zooming-shrinking technique. Proposed algorithm performance is evaluated in relation to standard JPEG algorithm. In order to envisage the effect of compression on classification performance, Maximum Likelihood, Mahalanobis and Minimum distance classifiers performance is evaluated with original image data, standard JPEG compressed data and the compressed image data with the proposed method. Experiments are carried out with multi-band images with various resolutions. Our experiments supports that the classification accuracies of compressed images are at par with original image data.
Maryam Sahami Gilani. 1970. \u201cA New Classification Performance Aware Multi sensor, Multi resolution Satellite image compression Technique\u201d. Global Journal of Computer Science and Technology - F: Graphics & Vision GJCST-F Volume 13 (GJCST Volume 13 Issue F7): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
Total Score: 93
Country: Iran
Subject: Global Journal of Computer Science and Technology - F: Graphics & Vision
Authors: Ch. Ramesh, Dr. N.B. Venkateswarlu, Dr. J.V.R. Murthy (PhD/Dr. count: 2)
View Count (all-time): 245
Total Views (Real + Logic): 25102
Total Downloads (simulated): 11157
Publish Date: 1970 01, Thu
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Neural Networks and Rules-based Systems used to Find Rational and
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Effective utilization of bandwidth and storage space is important in imaging applications including remote sensing. Remote sensing applications use multi-sensory, multi-band, multi resolution images. Usually, remote sensing applications uses image classification results for their analysis and decision making. In this paper we propose a new JPEG based image compression algorithm based on zooming-shrinking technique. Proposed algorithm performance is evaluated in relation to standard JPEG algorithm. In order to envisage the effect of compression on classification performance, Maximum Likelihood, Mahalanobis and Minimum distance classifiers performance is evaluated with original image data, standard JPEG compressed data and the compressed image data with the proposed method. Experiments are carried out with multi-band images with various resolutions. Our experiments supports that the classification accuracies of compressed images are at par with original image data.
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