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Image Classification based on Feature Extraction with AlexNet Architecture

Zarli Cho1 , Khin Myo Kyi2 , Kyi Thar Oo3

  1. University of Computer Studies, Taungoo, Myanmar.
  2. University of Computer Studies, Taungoo, Myanmar.
  3. University of Computer Studies, Thaton, Myanmar.

Section:Research Paper, Product Type: Journal Paper
Volume-8 , Issue-4 , Page no. 14-18, Apr-2020

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v8i4.1418

Online published on Apr 30, 2020

Copyright © Zarli Cho, Khin Myo Kyi, Kyi Thar Oo . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Zarli Cho, Khin Myo Kyi, Kyi Thar Oo, “Image Classification based on Feature Extraction with AlexNet Architecture,” International Journal of Computer Sciences and Engineering, Vol.8, Issue.4, pp.14-18, 2020.

MLA Style Citation: Zarli Cho, Khin Myo Kyi, Kyi Thar Oo "Image Classification based on Feature Extraction with AlexNet Architecture." International Journal of Computer Sciences and Engineering 8.4 (2020): 14-18.

APA Style Citation: Zarli Cho, Khin Myo Kyi, Kyi Thar Oo, (2020). Image Classification based on Feature Extraction with AlexNet Architecture. International Journal of Computer Sciences and Engineering, 8(4), 14-18.

BibTex Style Citation:
@article{Cho_2020,
author = {Zarli Cho, Khin Myo Kyi, Kyi Thar Oo},
title = {Image Classification based on Feature Extraction with AlexNet Architecture},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2020},
volume = {8},
Issue = {4},
month = {4},
year = {2020},
issn = {2347-2693},
pages = {14-18},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=5067},
doi = {https://doi.org/10.26438/ijcse/v8i4.1418}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v8i4.1418}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=5067
TI - Image Classification based on Feature Extraction with AlexNet Architecture
T2 - International Journal of Computer Sciences and Engineering
AU - Zarli Cho, Khin Myo Kyi, Kyi Thar Oo
PY - 2020
DA - 2020/04/30
PB - IJCSE, Indore, INDIA
SP - 14-18
IS - 4
VL - 8
SN - 2347-2693
ER -

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Abstract

Deep learning has emerged as a new area in machine learning and is applied to a number of signal and image applications. Although the existing traditional image classification methods have been widely applied in practical problems, such as unsatisfactory effects and weak adaptive ability. The main purpose of the work presented in this paper, is to apply the concept of image feature extraction with AlexNet Convolutional Neural Networks (CNN) in Digital Elevation Map and Topological Map boundary classification of Yangon City in Myanmar. The automated derivation of topographic data from DEMs is faster, less subjective and provides more reproducible measurements than traditional manual techniques applied to topographic maps. Data are acquired from the United States Geological Survey (USGS) database. This study is supposed to handle of geospatial information and production of maps. Geospatial users have to understand the distortion characteristics of each maps. The analysis of this result is revealed that has a good classification accuracy for all the tested maps based on the proposed system.

Key-Words / Index Term

AlexNet, CNN, Elevation Map, USGS

References

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