To: Author

Article Fingerprint
ReserarchID
CST8DAD3
Choose where you want to hide AI Takeaway. Your site-wide choice will be remembered in this browser.
Support vector machines have been used as a classification method in various domains including and not restricted to species distribution and land cover detection. Support vector machines offer many key advantages like its capacity to handle huge feature spaces and its flexibility in selecting a similarity function. In this paper the support vector machine classification method is applied to remote sensed data. Two different formats of remote sensed data is considered for the same. The first format is a comma separated value format wherein a classification model is developed to predict whether a specific bird species belongs to Darjeeling area or any other region. The second format used is raster format which contains image of Andhra Pradesh state in India.
Tarun Rao, T.V.Rajinikanth. 2014. "Supervised Classification of Remote Sensed Data using Support Vector Machine". Global Journal of Computer Science and Technology, Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 14 (GJCST Volume 14 Issue C1).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
Total Score: 142
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: Tarun Rao , T.V.Rajinikanth (PhD/Dr. count: 0)
View Count (all-time): 467
Total Views (Real + Logic): 3732
Total Downloads (simulated): 154
Publish Date: 2014 01, Wed
Monthly Totals (Real + Logic):
We use cookies and similar technologies to improve site performance, understand traffic, and enhance your publishing experience. Cookie Policy
Choose which optional cookies Global Journals can use. Your preference applies across this platform and can be updated any time.
These cookies are required for core website functionality and security.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.