Q Tang, J Liang, F Zhu - Signal Processing, 2023 - Elsevier
The wide deployment of multi-modal sensors in various areas generates vast amounts of data with characteristics of high volume, wide variety, and high integrity. However, traditional …
J Yao, B Zhang, C Li, D Hong… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The recent success of attention mechanism-driven deep models, like vision transformer (ViT) as one of the most representatives, has intrigued a wave of advanced research to explore …
Classification methods that are based on hyperspectral images (HSIs) are playing an increasingly significant role in the processes of target detection, environmental …
In recent years, convolutional neural networks (CNNs) have drawn significant attention for the classification of hyperspectral images (HSIs). Due to their self-attention mechanism, the …
Enormous efforts have been recently made to super-resolve hyperspectral (HS) images with the aid of high spatial resolution multispectral (MS) images. Most prior works usually perform …
G Zhao, Q Ye, L Sun, Z Wu, C Pan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The joint use of multisource remote-sensing (RS) data for Earth observation missions has drawn much attention. Although the fusion of several data sources can improve the accuracy …
Transformers have intrigued the vision research community with their state-of-the-art performance in natural language processing. With their superior performance, transformers …
K Ding, T Lu, W Fu, S Li, F Ma - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Hyperspectral images (HSIs) contain rich spatial and spectral detail information, while light detection and ranging (LiDAR) data can provide the elevation information. Thus, the fusion …
L Fang, Y Jiang, Y Yan, J Yue… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In recent years, hyperspectral image (HSI) classification and detection techniques based on deep learning have been widely applied to various aspects, such as environmental …