151 citations · 472 across the 49 of their papers we have counts for
14 papers · 1 filter
Multi-spatial Multi-temporal Air Quality Forecasting with Integrated Monitoring and Reanalysis Data
Yuxiao Hu, Qian Li, Xiaodan Shi +2
Accurate air quality forecasting is crucial for public health, environmental monitoring and protection, and urban planning. However, existing methods fail to effectively utilize mu…
Domain Prompt Learning with Quaternion Networks
Qinglong Cao, Zhengqin Xu, Yuntian Chen +2
Prompt learning has emerged as an effective and data-efficient technique in large Vision-Language Models (VLMs). However, when adapting VLMs to specialized domains such as remote s…
Focus on Hiders: Exploring Hidden Threats for Enhancing Adversarial Training
Qian Li, Yuxiao Hu, Yinpeng Dong +2
Adversarial training is often formulated as a min-max problem, however, concentrating only on the worst adversarial examples causes alternating repetitive confusion of the model, i…
CLeaRForecast: Contrastive Learning of High-Purity Representations for Time Series Forecasting
Jiaxin Gao, Yuxiao Hu, Qinglong Cao +2
Time series forecasting (TSF) holds significant importance in modern society, spanning numerous domains. Previous representation learning-based TSF algorithms typically embrace a c…
MoE-AMC: Enhancing Automatic Modulation Classification Performance Using Mixture-of-Experts
Jiaxin Gao, Qinglong Cao, Yuntian Chen
Automatic Modulation Classification (AMC) plays a vital role in time series analysis, such as signal classification and identification within wireless communications. Deep learning…
AS-XAI: Self-supervised Automatic Semantic Interpretation for CNN
Changqi Sun, Hao Xu, Yuntian Chen +1
Explainable artificial intelligence (XAI) aims to develop transparent explanatory approaches for "black-box" deep learning models. However,it remains difficult for existing methods…
A knowledge-based data-driven (KBDD) framework for all-day identification of cloud types using satellite remote sensing
Longfeng Nie, Yuntian Chen, Mengge Du +2
Cloud types, as a type of meteorological data, are of particular significance for evaluating changes in rainfall, heatwaves, water resources, floods and droughts, food security and…
QIENet: Quantitative irradiance estimation network using recurrent neural network based on satellite remote sensing data
Longfeng Nie, Yuntian Chen, Dongxiao Zhang +2
Global horizontal irradiance (GHI) plays a vital role in estimating solar energy resources, which are used to generate sustainable green energy. In order to estimate GHI with high…
Filtered Partial Differential Equations: a robust surrogate constraint in physics-informed deep learning framework
Dashan Zhang, Yuntian Chen, Shiyi Chen
Embedding physical knowledge into neural network (NN) training has been a hot topic. However, when facing the complex real-world, most of the existing methods still strongly rely o…
Reflection Invariance Learning for Few-shot Semantic Segmentation
Qinglong Cao, Yuntian Chen, Chao Ma +1
Few-shot semantic segmentation (FSS) aims to segment objects of unseen classes in query images with only a few annotated support images. Existing FSS algorithms typically focus on…
Interpretable AI-Driven Discovery of Terrain-Precipitation Relationships for Enhanced Climate Insights
Hao Xu, Yuntian Chen, Zhenzhong Zeng +3
Despite the remarkable strides made by AI-driven models in modern precipitation forecasting, these black-box models cannot inherently deepen the comprehension of underlying mechani…
Physics-constrained robust learning of open-form partial differential equations from limited and noisy data
Mengge Du, Yuntian Chen, Longfeng Nie +2
Unveiling the underlying governing equations of nonlinear dynamic systems remains a significant challenge. Insufficient prior knowledge hinders the determination of an accurate can…
Worth of knowledge in deep learning
Hao Xu, Yuntian Chen, Dongxiao Zhang
Knowledge constitutes the accumulated understanding and experience that humans use to gain insight into the world. In deep learning, prior knowledge is essential for mitigating sho…
Few-Shot Rotation-Invariant Aerial Image Semantic Segmentation
Qinglong Cao, Yuntian Chen, Chao Ma +1
Few-shot aerial image segmentation is a challenging task that involves precisely parsing objects in query aerial images with limited annotated support. Conventional matching method…