Enhance the Accuracy of Landslide Detection in UAV Images Using an Improved Mask R-CNN Model: A Case Study of Sanming, China

Extracting high-accuracy landslide areas using deep learning methods from high spatial resolution remote sensing images is a hot topic in current research. However, the existing deep learning algorithms are affected by background noise and landslide scale effects during the extraction process, leadi...

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Bibliographic Details
Main Authors:	Hua, L. (Author), Wang, D. (Author), Yun, L. (Author), Zhang, X. (Author), Zheng, Y. (Author)
Format:	Article
Language:	English
Published:	MDPI 2023
Subjects:	Aerial vehicle Aircraft detection Antennas CBAM Convolution Convolutional block attention module Convolutional neural network Convolutional neural networks deep learning Deep learning Extraction GA-region proposal network GA-RPN Genetic algorithms Image enhancement landslide Landslide detection Landslides Learning algorithms Learning systems Mask R-CNN Mask region-based convolutional neural network Neural network model Neural network models Region-based Remote sensing Unmanned aerial vehicles (UAV) Vehicle images
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Enhance the Accuracy of Landslide Detection in UAV Images Using an Improved Mask R-CNN Model: A Case Study of Sanming, China

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