[HTML][HTML] NCGLF2: Network combining global and local features for fusion of multisource remote sensing data
The fusion of multisource remote sensing (RS) data has demonstrated significant potential in
target recognition and classification tasks. However, there is limited emphasis on capturing …
target recognition and classification tasks. However, there is limited emphasis on capturing …
Multiscale 3-d–2-d mixed cnn and lightweight attention-free transformer for hyperspectral and lidar classification
The effective combination of hyperspectral image (HSI) and light detection and ranging
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …
(LiDAR) data can be used for land cover classification. Recently, deep-learning-based …
Common practices and taxonomy in deep multi-view fusion for remote sensing applications
The advances in remote sensing technologies have boosted applications for Earth
observation. These technologies provide multiple observations or views with different levels …
observation. These technologies provide multiple observations or views with different levels …
A novel graph-attention based multimodal fusion network for joint classification of hyperspectral image and LiDAR data
J Cai, M Zhang, H Yang, Y He, Y Yang, C Shi… - Expert Systems with …, 2024 - Elsevier
The joint classification of hyperspectral image (HSI) and Light Detection and Ranging
(LiDAR) data can provide complementary information for each other, which has become a …
(LiDAR) data can provide complementary information for each other, which has become a …
A joint convolutional cross ViT network for hyperspectral and light detection and ranging fusion classification
H Xu, T Zheng, Y Liu, Z Zhang, C Xue, J Li - Remote Sensing, 2024 - mdpi.com
The fusion of hyperspectral imagery (HSI) and light detection and ranging (LiDAR) data for
classification has received widespread attention and has led to significant progress in …
classification has received widespread attention and has led to significant progress in …
Joint Classification of Hyperspectral and LiDAR Data Using Height Information Guided Hierarchical Fusion-and-Separation Network
Hyperspectral image (HSI) and light detection and ranging (LiDAR) data are complementary
to each other, which can be combined to improve the classification performance. However …
to each other, which can be combined to improve the classification performance. However …
Relationship Learning from Multisource Images via Spatial-spectral Perception Network
Advances in multisource remote sensing have allowed for the development of more
comprehensive observation. The adoption of deep convolutional neural networks (CNN) …
comprehensive observation. The adoption of deep convolutional neural networks (CNN) …
Modality Fusion Vision Transformer for Hyperspectral and LiDAR Data Collaborative Classification
B Yang, X Wang, Y Xing, C Cheng… - IEEE Journal of …, 2024 - ieeexplore.ieee.org
In recent years, collaborative classification of multimodal data, eg, hyperspectral image (HSI)
and light detection and ranging (LiDAR), has been widely used to improve remote sensing …
and light detection and ranging (LiDAR), has been widely used to improve remote sensing …
Hyperspectral image classification using a new deep learning model based on pseudo-3D block and depth separable 2D–3D convolution
In the task of classification of hyperspectral images (HSI), standard 2D and 3D convolutions
increase the number of trainable parameters, making the model computationally complex …
increase the number of trainable parameters, making the model computationally complex …
Weakly Misalignment-free Adaptive Feature Alignment for UAVs-based Multimodal Object Detection
C Chen, J Qi, X Liu, K Bin, R Fu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Abstract Visible-infrared (RGB-IR) image fusion has shown great potentials in object
detection based on unmanned aerial vehicles (UAVs). However the weakly misalignment …
detection based on unmanned aerial vehicles (UAVs). However the weakly misalignment …