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Chaojun Ouyang

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Articles 5
Citations 18
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Recent Articles
1.
Zhang B, Ouyang C, Cui P, Xu Q, Wang D, Zhang F, et al.
Innovation (Camb) . 2024 Dec; 5(3):100617. PMID: 39677966
Streamflow and flood forecasting remains one of the long-standing challenges in hydrology. Traditional physically based models are hampered by sparse parameters and complex calibration procedures particularly in ungauged catchments. We...
2.
Zhao T, Wang S, Ouyang C, Chen M, Liu C, Zhang J, et al.
Innovation (Camb) . 2024 Sep; 5(5):100691. PMID: 39285902
This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection...
3.
Xu Q, Shi Y, Bamber J, Ouyang C, Zhu X
Water Res . 2024 Aug; 264:122162. PMID: 39126745
Large-scale hydrodynamic models generally rely on fixed-resolution spatial grids and model parameters as well as incurring a high computational cost. This limits their ability to accurately forecast flood crests and...
4.
Xu Y, Ouyang C, Xu Q, Wang D, Zhao B, Luo Y
Sci Data . 2024 Jan; 11(1):12. PMID: 38168493
In this work, we present the CAS Landslide Dataset, a large-scale and multisensor dataset for deep learning-based landslide detection, developed by the Artificial Intelligence Group at the Institute of Mountain...
5.
Wei K, Ouyang C, Duan H, Li Y, Chen M, Ma J, et al.
Innovation (Camb) . 2021 Sep; 1(2):100038. PMID: 34557712
No abstract available.