A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing

no code implementations • 1 Dec 2023 • Longfeng Nie, Yuntian Chen, Mengge Du, Changqi Sun, Dongxiao Zhang

Compared with widely used semantic segmentation networks, including SegNet, PSPNet, DeepLabV3+, UNet, and ResUnet, our proposed model CldNet with an accuracy of 80. 89+-2. 18% is state-of-the-art in identifying cloud types and has increased by 32%, 46%, 22%, 2%, and 39%, respectively.

Semantic Segmentation

QIENet: Quantitative irradiance estimation network using recurrent neural network based on satellite remote sensing data

no code implementations • 1 Dec 2023 • Longfeng Nie, Yuntian Chen, Dongxiao Zhang, Xinyue Liu, Wentian Yuan

Specifically, the temporal and spatial characteristics of remote sensing data of the satellite Himawari-8 are extracted and fused by recurrent neural network (RNN) and convolution operation, respectively.

Physics-constrained robust learning of open-form partial differential equations from limited and noisy data

1 code implementation • 14 Sep 2023 • Mengge Du, Yuntian Chen, Longfeng Nie, Siyu Lou, Dongxiao Zhang

The embedding phase integrates the initially identified PDE from the discovering process as a physical constraint into the predictive model for robust training.

Reinforcement Learning (RL)