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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: SATELLITE IMAGE SEGMENTATION AND CLASSIFICATION FOR ENVIRONMENTAL ANALYSIS
Authors Name: voddiparthy sandeep , Bhupathi Nagateja , Bollam Uday Kumar , Harsha sai
Unique Id: IJSDR2304143
Published In: Volume 8 Issue 4, April-2023
Abstract: Image segmentation is a challenging task in computer vision. This process includes the classification of visual input into segments to simplify image analysis. There are many types of methods for image segmentation some of the common methods are edge detection-based method region-based methods, clustering-based method, partial differential equation-based, watershed-based method, and neural network-based methods. This research work is mainly focused on image segmentation. Satellite images are given as the input of the proposed system. Machine learning techniques play a key role in various domains. Here the remotely sensed data can be segmented by using the K-Means clustering method. Compared with other traditional methods this clustering technique yields better results. This system can be implemented by using the MATLAB software tool. Machine learning concepts drastically decrease the time needed to arrange an exact map.
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Cite Article: "SATELLITE IMAGE SEGMENTATION AND CLASSIFICATION FOR ENVIRONMENTAL ANALYSIS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.828 - 832, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304143.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR2304143
Registration ID:205174
Published In: Volume 8 Issue 4, April-2023
DOI (Digital Object Identifier):
Page No: 828 - 832
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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