Meta-learning an intermediate representation for few-shot prediction of landslide susceptibility in large areas - Citegraph

Paper Info

Title
Meta-learning an intermediate representation for few-shot prediction of landslide susceptibility in large areas

Abstract
•A meta-learned representation is used for few-shot prediction of landslide susceptibility.•Unsupervised pretraining of unlabeled samples learn a discriminative embedding.•Weighing the contribution of each meta-tasks can solve inaccurate supervision problems.

Year	DOI	Venue
2022	10.1016/j.jag.2022.102807	International Journal of Applied Earth Observation and Geoinformation
Keywords	DocType	Volume
Landslide suceptibility,Block-wise analysis,Meta-learning,Few-shot adaption	Journal	110
ISSN	Citations	PageRank
1569-8432	0	0.34
References	Authors
2	10

Authors (10 rows)

Cited by (0 rows)

References (2 rows)

Name	Order	Citations	PageRank
Li Chen	1	5	32.61
Yulin Ding	2	0	0.34
Saeid Pirasteh	3	0	0.34
Han Hu	4	0	0.34
Zhu Qing	5	7	4.87
Xuming Ge	6	0	0.34
Haowei Zeng	7	0	0.34
Haojia Yu	8	0	0.34
Qisen Shang	9	0	0.34
Yongfei Song	10	0	0.34

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