From single-to multi-modal remote sensing imagery interpretation: A survey and taxonomy
Modality is a source or form of information. Through various modal information, humans can
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
perceive the world from multiple perspectives. Simultaneously, the observation of remote …
Automatic chart understanding: a review
Automated chart analysis has vast potential to improve the accessibility of charts for a wider
audience, eg, people with visual impairments or other disabilities, by generating captions for …
audience, eg, people with visual impairments or other disabilities, by generating captions for …
Extended vision transformer (ExViT) for land use and land cover classification: A multimodal deep learning framework
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 …
as one of the most representatives, has intrigued a wave of advanced research to explore …
[HTML][HTML] Multimodal remote sensing benchmark datasets for land cover classification with a shared and specific feature learning model
As remote sensing (RS) data obtained from different sensors become available largely and
openly, multimodal data processing and analysis techniques have been garnering …
openly, multimodal data processing and analysis techniques have been garnering …
UCSL: Toward unsupervised common subspace learning for cross-modal image classification
The emerging research line of cross-modal learning focuses on the issue of transferring
feature representation manner learned from limited multimodal data with labelings to the …
feature representation manner learned from limited multimodal data with labelings to the …
A cognitive IoT-based framework for effective diagnosis of COVID-19 using multimodal data
VP Jayachitra, S Nivetha, R Nivetha, R Harini - … Signal Processing and …, 2021 - Elsevier
The COVID-19 emerged at the end of 2019 and has become a global pandemic. There are
many methods for COVID-19 prediction using a single modality. However, none of them …
many methods for COVID-19 prediction using a single modality. However, none of them …
Feature matching and position matching between optical and SAR with local deep feature descriptor
Y Liao, Y Di, H Zhou, A Li, J Liu, M Lu… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Image matching between the optical and synthetic aperture radar (SAR) is one of the most
fundamental problems for earth observation. In recent years, many researchers have used …
fundamental problems for earth observation. In recent years, many researchers have used …
Geometric multimodal deep learning with multiscaled graph wavelet convolutional network
Multimodal data provide complementary information of a natural phenomenon by integrating
data from various domains with very different statistical properties. Capturing the …
data from various domains with very different statistical properties. Capturing the …
Deep Symmetric Fusion Transformer for Multimodal Remote Sensing Data Classification
In recent years, multimodal remote sensing data classification (MMRSC) has evoked
growing attention due to its more comprehensive and accurate delineation of Earth's surface …
growing attention due to its more comprehensive and accurate delineation of Earth's surface …
Shared manifold learning using a triplet network for multiple sensor translation and fusion with missing data
Heterogeneous data fusion can enhance the robustness and accuracy of an algorithm on a
given task. However, due to the difference in various modalities, aligning the sensors and …
given task. However, due to the difference in various modalities, aligning the sensors and …