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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This abstract proposed an algorithm for video denoising base on adaptive, pixel-wise, temporal averaging. This algorithm decomposes video signals into the set of 1-D time dependent signals and then removes the noise via establish the temporal averaging intervals during each signal from the set. Temporal averaging intervals established by simple, effective evaluation process which contain two-way thresholding. The proposed algorithm is experienced on quite a few types of 1-D signals and benchmark videos. Experiments advise that the proposed algorithm, regardless of its ease, produces high-quality denoising results.
Himanshu Makkar. 2018. \u201cRemoval of Noise from Video Signals using Adaptive Temporal Averaging\u201d. Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 17 (GJRE Volume 17 Issue F8): .
Crossref Journal DOI 10.17406/gjre
Print ISSN 0975-5861
e-ISSN 2249-4596
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: India
Subject: Global Journal of Research in Engineering - F: Electrical & Electronic
Authors: Himanshu Makkar, Prof. Onkar Singh Lamba (PhD/Dr. count: 0)
View Count (all-time): 196
Total Views (Real + Logic): 3280
Total Downloads (simulated): 1672
Publish Date: 2018 01, Mon
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Neural Networks and Rules-based Systems used to Find Rational and
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This abstract proposed an algorithm for video denoising base on adaptive, pixel-wise, temporal averaging. This algorithm decomposes video signals into the set of 1-D time dependent signals and then removes the noise via establish the temporal averaging intervals during each signal from the set. Temporal averaging intervals established by simple, effective evaluation process which contain two-way thresholding. The proposed algorithm is experienced on quite a few types of 1-D signals and benchmark videos. Experiments advise that the proposed algorithm, regardless of its ease, produces high-quality denoising results.
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