Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward

D Tuia, K Schindler, B Demir, XX Zhu… - … and Remote Sensing …, 2024‏ - ieeexplore.ieee.org
Earth observation (EO) is increasingly used for map** and monitoring processes
occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a …

Cooperative perception with V2V communication for autonomous vehicles

H Ngo, H Fang, H Wang - IEEE Transactions on Vehicular …, 2023‏ - ieeexplore.ieee.org
Occlusion is a critical problem in the Autonomous Driving System. Solving this problem
requires robust collaboration among autonomous vehicles traveling on the same roads …

There are no data like more data: Datasets for deep learning in earth observation

M Schmitt, SA Ahmadi, Y Xu, G Taşkin… - … and Remote Sensing …, 2023‏ - ieeexplore.ieee.org
Carefully curated and annotated datasets are the foundation of machine learning (ML), with
particularly data-hungry deep neural networks forming the core of what is often called …

2023 ieee grss data fusion contest: Large-scale fine-grained building classification for semantic urban reconstruction [technical committees]

C Persello, R Hänsch, G Vivone, K Chen… - … and Remote Sensing …, 2023‏ - ieeexplore.ieee.org
Buildings are essential components of urban areas. While research on the extraction and 3D
reconstruction of buildings is widely conducted, information on the fine-grained roof types of …

[HTML][HTML] ResDepth: A deep residual prior for 3D reconstruction from high-resolution satellite images

C Stucker, K Schindler - ISPRS Journal of Photogrammetry and Remote …, 2022‏ - Elsevier
Modern optical satellite sensors enable high-resolution stereo reconstruction from space.
But the challenging imaging conditions when observing the Earth from space push stereo …

The outcome of the 2021 ieee grss data fusion contest—track msd: Multitemporal semantic change detection

Z Li, F Lu, H Zhang, L Tu, J Li, X Huang… - IEEE Journal of …, 2022‏ - ieeexplore.ieee.org
We present here the scientific outcomes of the 2021 Data Fusion Contest (DFC2021)
organized by the Image Analysis and Data Fusion Technical Committee of the IEEE …

Learning mutual modulation for self-supervised cross-modal super-resolution

X Dong, N Yokoya, L Wang, T Uezato - European Conference on …, 2022‏ - Springer
Self-supervised cross-modal super-resolution (SR) can overcome the difficulty of acquiring
paired training data, but is challenging because only low-resolution (LR) source and high …

A mutual information domain adaptation network for remotely sensed semantic segmentation

H Chen, H Zhang, G Yang, S Li… - IEEE Transactions on …, 2022‏ - ieeexplore.ieee.org
Although deep learning has made semantic segmentation of very-high-resolution (VHR)
remote sensing (RS) images practical and efficient, its large-scale application is still limited …

THE benchmark: Transferable representation learning for monocular height estimation

Z **ong, W Huang, J Hu, XX Zhu - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Generating 3-D city models rapidly is crucial for many applications. Monocular height
estimation (MHE) is one of the most efficient and timely ways to obtain large-scale geometric …

SyntCities: A large synthetic remote sensing dataset for disparity estimation

MF Reyes, P d'Angelo… - IEEE Journal of Selected …, 2022‏ - ieeexplore.ieee.org
Studies in the last years have proved the outstanding performance of deep learning for
computer vision tasks in the remote sensing field, such as disparity estimation. However …