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.
|Number of pages||1|
|Publication status||Published - 17 May 2019|
|Event||ESA Living Planet Symposium 2019 - Milano Congressi, Milan, Italy|
Duration: 13 May 2019 → 17 May 2019
|Conference||ESA Living Planet Symposium 2019|
|Period||13/05/19 → 17/05/19|
Ghorbanzadeh, O., Blaschke, T., & Meena, S. R. (2019). Potential of Convolutional Neural Networks for earthquake‐triggered mass movement detection using optical and SAR data. Poster session presented at ESA Living Planet Symposium 2019, Milan, Italy. https://doi.org/10.13140/RG.2.2.16742.68165/1