17 citations · 26 across the 14 of their papers we have counts for
15 papers
Structured Neural Modeling of Daily Arctic Sea-Ice Concentration Evolution: Physical-Trajectory-Driven Learning and Forecast-Domain Adaptation
Maqun Zhang, Feng Gao, Wankun Chen +3
Accurate modeling of the daily evolution of sea ice concentration (SIC) is central to improving the credibility and operational forecasting capability of deep learning-based sea ic…
One-Step Evolution for Long-Time Extrapolation: An Error-Bound-Informed and Prior-Guided Neural Residual Framework for Autonomous PDEs
Maqun Zhang, Feng Gao, Wankun Chen +3
Accurate simulation of the long-time evolution of systems governed by partial differential equations (PDEs) is central to scientific computing. Among existing deep learning?based a…
Physics-Knowledge-Guided Hybrid Neural Learning for Arctic Sea Ice Concentration Evolution and Short-Range Prediction
Maqun Zhang, Feng Gao, Wankun Chen +3
Accurate modeling of sea ice concentration (SIC) evolution is essential for polar climate assessment and short?range sea ice prediction. Numerical and data-driven approaches consti…
Dual-Branch State-Displacement Network for Sea Surface Temperature Super-Resolution
Wankun Chen, Feng Gao, Yanhai Gan +4
Sea surface temperature (SST) is a critical indicator of global climate change, yet satellite-derived SST imagery often suffers from coarse spatial resolution, limiting the ability…
Incomplete Observations Boost Evolutionary Performance in Ocean Modeling
Yangyang Kong, Yutong Jiang, Yanhai Gan +3
Data-driven methods have revolutionized ocean modeling, yet current approaches rely heavily on complete reanalysis datasets, imposing computational constraints and limiting model p…
Axial-Relation Guided Fusion State Space Model for Optical-Elevation Sensing Image Segmentation
Feng Gao, Zhilin Jin, Yanhai Gan +2
Semantic segmentation of multi-source remote sensing images is a fundamental task for Earth observation applications. Existing methods often struggle with insufficient multi-scale…
Frequency-Enhanced Hilbert Scanning Mamba for Short-Term Arctic Sea Ice Concentration Prediction
Feng Gao, Zheng Gong, Wenli Liu +4
While Mamba models offer efficient sequence modeling, vanilla versions struggle with temporal correlations and boundary details in Arctic sea ice concentration (SIC) prediction. To…
Explore the Ideology of Deep Learning in ENSO Forecasts
Yanhai Gan, Yipeng Chen, Ning Li +3
The El Ni{~n}o-Southern Oscillation (ENSO) exerts profound influence on global climate variability, yet its prediction remains a grand challenge. Recent advances in deep learning h…
Wavelet-Assisted Mamba for Satellite-Derived Sea Surface Temperature Super-Resolution
Wankun Chen, Feng Gao, Yanhai Gan +3
Sea surface temperature (SST) is an essential indicator of global climate change and one of the most intuitive factors reflecting ocean conditions. Obtaining high-resolution SST da…
Frequency-Compensated Network for Daily Arctic Sea Ice Concentration Prediction
Jialiang Zhang, Feng Gao, Yanhai Gan +2
Accurately forecasting sea ice concentration (SIC) in the Arctic is critical to global ecosystem health and navigation safety. However, current methods still is confronted with two…
Arctic Sea Ice Image Super-Resolution Based on Multi-Scale Convolution and Dual-Gating Mechanism
Zhaomin Fang, Wankun Chen, Feng Gao +3
Arctic Sea Ice Concentration (SIC) is the ratio of ice-covered area to the total sea area of the Arctic Ocean, which is a key indicator for maritime activities. Nowadays, we often…
LSKSANet: A Novel Architecture for Remote Sensing Image Semantic Segmentation Leveraging Large Selective Kernel and Sparse Attention Mechanism
Miao Fu, Feng Gao, Ruzhuang Hua +3
In this paper, we proposed large selective kernel and sparse attention network (LSKSANet) for remote sensing image semantic segmentation. The LSKSANet is a lightweight network that…
Learning the Precise Feature for Cluster Assignment
Yanhai Gan, Xinghui Dong, Huiyu Zhou +2
Clustering is one of the fundamental tasks in computer vision and pattern recognition. Recently, deep clustering methods (algorithms based on deep learning) have attracted wide att…
Perception Driven Texture Generation
Yanhai Gan, Huifang Chi, Ying Gao +3
This paper investigates a novel task of generating texture images from perceptual descriptions. Previous work on texture generation focused on either synthesis from examples or gen…
A PCA-Based Convolutional Network
Yanhai Gan, Jun Liu, Junyu Dong +1
In this paper, we propose a novel unsupervised deep learning model, called PCA-based Convolutional Network (PCN). The architecture of PCN is composed of several feature extraction…