Dual-Branch Subpixel-Guided Network for Hyperspectral Image Classification
Deep learning (DL) has been widely applied into hyperspectral image (HSI) classification
owing to its promising feature learning and representation capabilities. However, limited by …
owing to its promising feature learning and representation capabilities. However, limited by …
Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary
In a hyperspectral image, there is a close correlation between spectra and a certain degree
of correlation in the pixel space. However, most existing low-rank representation (LRR) …
of correlation in the pixel space. However, most existing low-rank representation (LRR) …
Few-Shot Incremental Object Detection in Aerial Imagery via Dual-Frequency Prompt
Recently, there has been a growing interest in few-shot incremental object detection
(FSIOD). It learns new tasks with limited data while mitigating catastrophic forgetting on …
(FSIOD). It learns new tasks with limited data while mitigating catastrophic forgetting on …
ConvGRU-based Multi-scale Frequency Fusion Network for PAN-MS Joint Classification
As a hot research topic in remote sensing, effectively integrating the advantageous features
of multi-spectral and panchromatic images is the main challenge for fusing these two remote …
of multi-spectral and panchromatic images is the main challenge for fusing these two remote …
[PDF][PDF] Hyperspectral Anomaly Detection via Low-Rank Representation with Dual Graph Regularizations and Adaptive Dictionary. Remote Sens. 2024, 16, 1837
X Cheng, R Mu, S Lin, M Zhang, H Wang - 2024 - researchgate.net
In a hyperspectral image, there is a close correlation between spectra and a certain degree
of correlation in the pixel space. However, most existing low-rank representation (LRR) …
of correlation in the pixel space. However, most existing low-rank representation (LRR) …