Cross-scene wetland map** on hyperspectral remote sensing images using adversarial domain adaptation network
Wetlands are one of the most important ecosystems on the Earth, and using hyperspectral
remote sensing (RS) technology for fine wetland map** is important for restoring and …
remote sensing (RS) technology for fine wetland map** is important for restoring and …
Class-aligned and class-balancing generative domain adaptation for hyperspectral image classification
The task of hyperspectral image (HSI) classification is fundamental and crucial in HSI
processing. Currently, domain adaptive methods have become a research hotspot in HSI …
processing. Currently, domain adaptive methods have become a research hotspot in HSI …
Category-specific prototype self-refinement contrastive learning for few-shot hyperspectral image classification
Deep learning (DL) has been extensively used for hyperspectral image classification (HSIC)
with significant success, but the classification of high-dimensional hyperspectral image (HSI) …
with significant success, but the classification of high-dimensional hyperspectral image (HSI) …
Adversarial domain alignment with contrastive learning for hyperspectral image classification
F Liu, W Gao, J Liu, X Tang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, deep learning-based hyperspectral image (HSI) classification techniques are
flourishing and exhibit good performance, where cross-domain information is usually utilized …
flourishing and exhibit good performance, where cross-domain information is usually utilized …
Hyperspectral image change detection based on gated spectral–spatial–temporal attention network with spectral similarity filtering
Hyperspectral imaging enables advanced change detection (CD) but struggles with
extensive redundant data across spatial and spectral dimensions. This bloats model size …
extensive redundant data across spatial and spectral dimensions. This bloats model size …
Few-shot object detection in remote sensing images via label-consistent classifier and gradual regression
Y Liu, Z Pan, J Yang, B Zhang, G Zhou… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the abomination of time-consuming or even impractical large-scale labeling, few-shot
object detection (FSOD) based on natural scenes has attracted extensive attention …
object detection (FSOD) based on natural scenes has attracted extensive attention …
TMCFN: Text-supervised multidimensional contrastive fusion network for hyperspectral and LiDAR classification
The joint classification of hyperspectral images (HSIs) and LiDAR data plays a crucial role in
Earth observation missions. Most advanced methods are based on discrete label …
Earth observation missions. Most advanced methods are based on discrete label …
A decoder-focused multitask network for semantic change detection
Z Li, X Wang, S Fang, J Zhao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Recently, semantic change detection (SCD) has gained growing attention from the remote-
sensing (RS) research community due to its critical role in Earth observation applications …
sensing (RS) research community due to its critical role in Earth observation applications …
Contrastive learning based on category matching for domain adaptation in hyperspectral image classification
Y Ning, J Peng, Q Liu, Y Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Cross-scene hyperspectral image classification (HSIC) is a challenging topic in remote
sensing, especially when there are no labels in the target domain. Domain adaptation (DA) …
sensing, especially when there are no labels in the target domain. Domain adaptation (DA) …
Foundation model-based multimodal remote sensing data classification
With the increasing availability and openness of remote sensing (RS) data collected from
diverse sensors, there has been a growing interest in multimodal RS data classification …
diverse sensors, there has been a growing interest in multimodal RS data classification …