Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data

Omid Ghorbanzadeh; Thomas Blaschke; Sansar Raj Meena

doi:10.13140/RG.2.2.16742.68165/1

Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data

Omid Ghorbanzadeh, Thomas Blaschke, Sansar Raj Meena

Research output: Contribution to conference › Poster › Academic

Abstract

While Convolutional Neural Networks (CNNs) have reached good accuracies for object recognition in aerial images, only a few studies exist that use deep-learning methods and CNNs for landslide detection. The impact of using different input training data on landslide detection by the CNNs is unclear.

Original language	English
Number of pages	1
DOIs	https://doi.org/10.13140/RG.2.2.16742.68165/1
Publication status	Published - 17 May 2019
Externally published	Yes
Event	ESA Living Planet Symposium 2019 - Milano Congressi, Milan, Italy Duration: 13 May 2019 → 17 May 2019 https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19

Conference

Conference	ESA Living Planet Symposium 2019
Country/Territory	Italy
City	Milan
Period	13/05/19 → 17/05/19
Internet address	https://lps19.esa.int/NikalWebsitePortal/living-planet-symposium-2019/lps19

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title = "Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data",

abstract = "While Convolutional Neural Networks (CNNs) have reached good accuracies for object recognition in aerial images, only a few studies exist that use deep-learning methods and CNNs for landslide detection. The impact of using different input training data on landslide detection by the CNNs is unclear.",

author = "Omid Ghorbanzadeh and Thomas Blaschke and Meena, \{Sansar Raj\}",

year = "2019",

month = may,

day = "17",

doi = "10.13140/RG.2.2.16742.68165/1",

language = "English",

note = "ESA Living Planet Symposium 2019 ; Conference date: 13-05-2019 Through 17-05-2019",

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TY - CONF

T1 - Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data

AU - Ghorbanzadeh, Omid

AU - Blaschke, Thomas

AU - Meena, Sansar Raj

PY - 2019/5/17

Y1 - 2019/5/17

N2 - While Convolutional Neural Networks (CNNs) have reached good accuracies for object recognition in aerial images, only a few studies exist that use deep-learning methods and CNNs for landslide detection. The impact of using different input training data on landslide detection by the CNNs is unclear.

AB - While Convolutional Neural Networks (CNNs) have reached good accuracies for object recognition in aerial images, only a few studies exist that use deep-learning methods and CNNs for landslide detection. The impact of using different input training data on landslide detection by the CNNs is unclear.

U2 - 10.13140/RG.2.2.16742.68165/1

DO - 10.13140/RG.2.2.16742.68165/1

M3 - Poster

T2 - ESA Living Planet Symposium 2019

Y2 - 13 May 2019 through 17 May 2019

ER -

Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data

Abstract

Conference

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