Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images

Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images

Recent advancements in deep convolutional neural networks (DCNNs) have significantly improved landslides identification using remote sensing images. Pixel-wise semantic segmentation (PSS) and object-oriented detection (OOD) are two dominant approaches, wherein PSS are better as providing detailed de...

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Bibliographic Details
Main Authors: Zheng Han, Bangjie Fu, Zhenxiong Fang, Yange Li, Jiaying Li, Nan Jiang, Guangqi Chen
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Landslide
semantic segmentation
deep convolutional neural networks
Dynahead-YOLO model
Otsu binarization method
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2024.2398103
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https://www.tandfonline.com/doi/10.1080/19475705.2024.2398103

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