RIPF-Unet for regional landslides detection: a novel deep learning model boosted by reversed image pyramid features-Reference-Cited by-同舟云学术

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RIPF-Unet for regional landslides detection: a novel deep learning model boosted by reversed image pyramid features

Published:2023-08-28 Issue:1 Volume:119 Page:701-719
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Fu Bangjie,Li Yange,Han Zheng^ORCID,Fang Zhenxiong,Chen Ningsheng,Hu Guisheng,Wang Weidong

Funder

the National Key R&D Program of China

the National Natural Science Foundation of China

the Natural Science Foundation for Excellent Young Scholars of Hunan

the Innovation Provincial Program of Hunan Province

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-023-06145-0.pdf

Reference78 articles.

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2. Altamirano A, Miranda A, Aplin P, Carrasco J, Catalan G, Cayuela L, Fuentes-Castillo T, Hernandez A, Martínez-Harms MJ, Peluso F (2020) Natural forests loss and tree plantations: large-scale tree cover loss differentiation in a threatened biodiversity hotspot. Environ Res Lett 15:124055. https://doi.org/10.1088/1748-9326/abca64

3. Badrinarayanan V, Kendall A, Cipolla R (2017) SegNet: a deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans Pattern Anal Mach Intell 39:2481–2495. https://doi.org/10.1109/TPAMI.2016.2644615

4. Barak S, Imamalipour A, Abedi M, Bahroudi A, Khalifani FM (2021) Comprehensive modeling of mineral potential mapping by integration of multiset geosciences data. Geochemistry 81:125824. https://doi.org/10.1016/j.chemer.2021.125824

5. Behling R, Roessner S, Golovko D, Kleinschmit B (2016) Derivation of long-term spatiotemporal landslide activity-A multi-sensor time series approach. Remote Sens Environ 186:88–104. https://doi.org/10.1016/j.rse.2016.07.017

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1. Dynahead-YOLO-Otsu: an efficient DCNN-based landslide semantic segmentation method using remote sensing images;Geomatics, Natural Hazards and Risk;2024-09-02

2. A side-sampling based Linformer model for landslide susceptibility assessment: a case study of the railways in China;Geomatics, Natural Hazards and Risk;2024-05-24

3. Enhancing Landslide Segmentation with Guide Attention Mechanism and Fast Fourier Transformer;Lecture Notes in Computer Science;2024

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