InCR: Inception and concatenation residual block-based deep learning network for damaged building detection using remote sensing images
<p dir="ltr">In February 2023, Turkey experienced a series of earthquakes that caused significant damage to buildings and affected many people. Detecting building damage quickly is crucial for helping earthquake victims, and we believe machine learning models offer a promising soluti...
Saved in:
| Main Author: | Burak Tasci (17032302) (author) |
|---|---|
| Other Authors: | Madhav R. Acharya (17032305) (author), Mehmet Baygin (17032308) (author), Sengul Dogan (16677969) (author), Turker Tuncer (16677966) (author), Samir Brahim Belhaouari (9427347) (author) |
| Published: |
2023
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Seismic risk quantification and GIS-based seismic risk maps for Dubai-UAE_Dataset
by: AlHamaydeh, Mohammad
Published: (2021) -
Unique jet determination of CR maps into Nash sets
by: Bernhard Lamel (14152263)
Published: (2023) -
Phytoextraction of Cr(VI) from soil using Portulaca oleracea
by: Alyazouri, Ayman
Published: (2014) -
A special characteristic of an earthquake response spectrum detected in Turkey
by: Mohammad Zaher Serdar (17191381)
Published: (2022) -
Physical and Corrosion Properties of CoCrNi Medium Entropy Alloy Thin Films
by: Mohamed, Omer Fathalrahman
Published: (2021)