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Path Loss Exponent and Shadowing Factor Prediction From Satellite Images Using Deep Learning
IEEE Access
◽
10.1109/access.2019.2931072
◽
2019
◽
Vol 7
◽
pp. 101366-101375
◽
Cited By ~ 3
Author(s):
Hasan F. Ates
◽
Syed Muhammad Hashir
◽
Tuncer Baykas
◽
Bahadir K. Gunturk
Keyword(s):
Deep Learning
◽
Satellite Images
◽
Path Loss
◽
Path Loss Exponent
Download Full-text
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References
Predicting Path Loss Distribution of an Area From Satellite Images Using Deep Learning
IEEE Access
◽
10.1109/access.2020.2985929
◽
2020
◽
Vol 8
◽
pp. 64982-64991
◽
Cited By ~ 1
Author(s):
Omar Ahmadien
◽
Hasan F. Ates
◽
Tuncer Baykas
◽
Bahadir K. Gunturk
Keyword(s):
Deep Learning
◽
Satellite Images
◽
Path Loss
◽
Loss Distribution
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Analysis of deep learning based path loss prediction from satellite images
2021 29th Signal Processing and Communications Applications Conference (SIU)
◽
10.1109/siu53274.2021.9478009
◽
2021
◽
Author(s):
Muhammad Z. Alam
◽
Hasan F. Ates
◽
Tuncer Baykas
◽
Bahadir K. Gunturk
Keyword(s):
Deep Learning
◽
Satellite Images
◽
Path Loss
◽
Loss Prediction
◽
Path Loss Prediction
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Path Loss Exponent Prediction for Outdoor Millimeter Wave Channels through Deep Learning
2019 IEEE Wireless Communications and Networking Conference (WCNC)
◽
10.1109/wcnc.2019.8885668
◽
2019
◽
Cited By ~ 1
Author(s):
JunG-Yong Lee
◽
Min Young Kang
◽
Seong-Cheol Kim
Keyword(s):
Deep Learning
◽
Millimeter Wave
◽
Path Loss
◽
Path Loss Exponent
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Crowdsourcing-based application to solve the problem of insufficient training data in deep learning-based classification of satellite images
Geocarto International
◽
10.1080/10106049.2021.1917006
◽
2021
◽
pp. 1-17
Author(s):
Ekrem Saralioglu
◽
Oguz Gungor
Keyword(s):
Deep Learning
◽
Satellite Images
◽
Training Data
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Accurate Distance Estimation for RSS Localization With Statistical Path Loss Exponent Model
GLOBECOM 2020 - 2020 IEEE Global Communications Conference
◽
10.1109/globecom42002.2020.9348254
◽
2020
◽
Author(s):
K. N. R. Surya Vara Prasad
◽
Jiaming Cheng
◽
Vijay K. Bhargava
Keyword(s):
Path Loss
◽
Distance Estimation
◽
Path Loss Exponent
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Fusing Diverse Input Modalities for Path Loss Prediction: A Deep Learning Approach
IEEE Access
◽
10.1109/access.2021.3059589
◽
2021
◽
Vol 9
◽
pp. 30441-30451
Author(s):
Sotirios P. Sotiroudis
◽
Panagiotis Sarigiannidis
◽
Sotirios K. Goudos
◽
Katherine Siakavara
Keyword(s):
Deep Learning
◽
Path Loss
◽
Learning Approach
◽
Loss Prediction
◽
Path Loss Prediction
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Deep Learning for Wave Height Classification in Satellite Images for Offshore Wind Access
Data Analytics for Renewable Energy Integration. Technologies, Systems and Society - Lecture Notes in Computer Science
◽
10.1007/978-3-030-04303-2_6
◽
2018
◽
pp. 83-93
Author(s):
Ryan J. Spick
◽
James A. Walker
Keyword(s):
Deep Learning
◽
Wave Height
◽
Satellite Images
◽
Offshore Wind
Download Full-text
Improving the precision of RSSI-based low-energy localization using path loss exponent estimation
2014 11th Workshop on Positioning, Navigation and Communication (WPNC)
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10.1109/wpnc.2014.6843302
◽
2014
◽
Cited By ~ 10
Author(s):
Ali Golestani
◽
Neda Petreska
◽
Dennis Wilfert
◽
Christopher Zimmer
Keyword(s):
Path Loss
◽
Low Energy
◽
Energy Localization
◽
Path Loss Exponent
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Path loss exponent estimation in large wireless networks
2009 Information Theory and Applications Workshop
◽
10.1109/ita.2009.5044933
◽
2009
◽
Cited By ~ 25
Author(s):
S. Srinivasa
◽
M. Haenggi
Keyword(s):
Wireless Networks
◽
Path Loss
◽
Path Loss Exponent
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Deep Learning with Satellite Images and Volunteered Geographic Information
Geospatial Data Science Techniques and Applications
◽
10.1201/9781315228396-4
◽
2017
◽
pp. 63-78
Author(s):
Jiaoyan Chen
◽
Alexander Zipf
Keyword(s):
Deep Learning
◽
Satellite Images
◽
Volunteered Geographic Information
◽
Geographic Information
Download Full-text
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