229 citations · 423 across the 11 of their papers we have counts for
11 papers
MambaMoE: Mixture-of-Spectral-Spatial-Experts State Space Model for Hyperspectral Image Classification
Yichu Xu, Di Wang, Hongzan Jiao +2
Mamba-based models have recently demonstrated significant potential in hyperspectral image (HSI) classification, primarily due to their ability to perform contextual modeling with…
Dual Selective Fusion Transformer Network for Hyperspectral Image Classification
Yichu Xu, Di Wang, Lefei Zhang +1
Transformer has achieved satisfactory results in the field of hyperspectral image (HSI) classification. However, existing Transformer models face two key challenges when dealing wi…
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model
Di Wang, Meiqi Hu, Yao Jin +19
Accurate hyperspectral image (HSI) interpretation is critical for providing valuable insights into various earth observation-related applications such as urban planning, precision…
MTP: Advancing Remote Sensing Foundation Model via Multi-Task Pretraining
Di Wang, Jing Zhang, Minqiang Xu +8
Foundation models have reshaped the landscape of Remote Sensing (RS) by enhancing various image interpretation tasks. Pretraining is an active research topic, encompassing supervis…
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model
Di Wang, Jing Zhang, Bo Du +4
The success of the Segment Anything Model (SAM) demonstrates the significance of data-centric machine learning. However, due to the difficulties and high costs associated with anno…
Empowering Agrifood System with Artificial Intelligence: A Survey of the Progress, Challenges and Opportunities
Tao Chen, Liang Lv, Di Wang +12
With the world population rapidly increasing, transforming our agrifood systems to be more productive, efficient, safe, and sustainable is crucial to mitigate potential food shorta…
HKNAS: Classification of Hyperspectral Imagery Based on Hyper Kernel Neural Architecture Search
Di Wang, Bo Du, Liangpei Zhang +1
Recent neural architecture search (NAS) based approaches have made great progress in hyperspectral image (HSI) classification tasks. However, the architectures are usually optimize…
DCN-T: Dual Context Network with Transformer for Hyperspectral Image Classification
Di Wang, Jing Zhang, Bo Du +2
Hyperspectral image (HSI) classification is challenging due to spatial variability caused by complex imaging conditions. Prior methods suffer from limited representation ability, a…
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
Di Wang, Qiming Zhang, Yufei Xu +4
Large-scale vision foundation models have made significant progress in visual tasks on natural images, with vision transformers being the primary choice due to their good scalabili…
An Empirical Study of Remote Sensing Pretraining
Di Wang, Jing Zhang, Bo Du +2
Deep learning has largely reshaped remote sensing (RS) research for aerial image understanding and made a great success. Nevertheless, most of the existing deep models are initiali…
Spectral-Spatial Global Graph Reasoning for Hyperspectral Image Classification
Di Wang, Bo Du, Liangpei Zhang
Convolutional neural networks have been widely applied to hyperspectral image classification. However, traditional convolutions can not effectively extract features for objects wit…