Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
Article Fingerprint
ReserarchID
CSTSDE9232D
Image processing methodologies and domain is quite wide and really efficient now days for real time applications. Our work primarily deals with the domain of image segmentation and using segmentation concept, texture recognition has been performed with comparative results and simulations performed over a particular image dataset. The initial work in our proposed work is to perform segmentation on each part image then performing extraction .We have focused on segmentation followed by extraction so that the classification result may not contain much error. The conventional approach has been implemented in this regard first and then the main problem that has been formulated is patch up data pixels together which provide error in getting right and appropriate texture. In order to deal with the problem formulated in the existing work we have proposed a new commuted method in which the extraction and segmentation of image depends on the dynamic threshold set by user.
Divya Mathur. 2019. \u201cA Collaborative approach for segmentation of probe image for efficient texture recognition\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 19 (GJCST Volume 19 Issue C1): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Neural Networks and Rules-based Systems used to Find Rational and
A Comparative Study of the Effeect of Promotion on Employee
The Problem Managing Bicycling Mobility in Latin American Cities: Ciclovias
Impact of Capillarity-Induced Rising Damp on the Energy Performance of
Image processing methodologies and domain is quite wide and really efficient now days for real time applications. Our work primarily deals with the domain of image segmentation and using segmentation concept, texture recognition has been performed with comparative results and simulations performed over a particular image dataset. The initial work in our proposed work is to perform segmentation on each part image then performing extraction .We have focused on segmentation followed by extraction so that the classification result may not contain much error. The conventional approach has been implemented in this regard first and then the main problem that has been formulated is patch up data pixels together which provide error in getting right and appropriate texture. In order to deal with the problem formulated in the existing work we have proposed a new commuted method in which the extraction and segmentation of image depends on the dynamic threshold set by user.
We are currently updating this article page for a better experience.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
