Artificial Intelligence to Advance Earth Observation: A review of models, recent trends, and pathways forward
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 …
occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a …
Recent developments of content-based image retrieval (CBIR)
X Li, J Yang, J Ma - Neurocomputing, 2021 - Elsevier
With the development of Internet technology and the popularity of digital devices, Content-
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …
Based Image Retrieval (CBIR) has been quickly developed and applied in various fields …
BigEarthNet-MM: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval [software and data sets]
G Sumbul, A De Wall, T Kreuziger… - … and Remote Sensing …, 2021 - ieeexplore.ieee.org
This article presents the multimodal BigEarthNet (BigEarthNet-MM) benchmark archive
consisting of 590,326 pairs of Sentinel-1 and Sentinel-2 image patches to support deep …
consisting of 590,326 pairs of Sentinel-1 and Sentinel-2 image patches to support deep …
Image retrieval from remote sensing big data: A survey
The blooming proliferation of aeronautics and astronautics platforms, together with the ever-
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
increasing remote sensing imaging sensors on these platforms, has led to the formation of …
Meta-hashing for remote sensing image retrieval
With the explosive growth of the volume and resolution of high-resolution remote-sensing
(HRRS) images, the management of them becomes a challenging task. The traditional …
(HRRS) images, the management of them becomes a challenging task. The traditional …
A self-supervised-driven open-set unsupervised domain adaptation method for optical remote sensing image scene classification and retrieval
S Wang, D Hou, H **ng - IEEE Transactions on Geoscience …, 2023 - ieeexplore.ieee.org
Unsupervised domain adaptation (UDA) is an important solution to reduce the bias between
the labeled source domain and the unlabeled target domain. It has attracted more attention …
the labeled source domain and the unlabeled target domain. It has attracted more attention …
Deep unsupervised contrastive hashing for large-scale cross-modal text-image retrieval in remote sensing
Due to the availability of large-scale multi-modal data (eg, satellite images acquired by
different sensors, text sentences, etc) archives, the development of cross-modal retrieval …
different sensors, text sentences, etc) archives, the development of cross-modal retrieval …
Unsupervised contrastive hashing for cross-modal retrieval in remote sensing
The development of cross-modal retrieval systems that can search and retrieve semantically
relevant data across different modalities based on a query in any modality has attracted …
relevant data across different modalities based on a query in any modality has attracted …
Unsupervised deep hashing through learning soft pseudo label for remote sensing image retrieval
Unsupervised hashing is an important approach for large-scale content-based remote
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …
sensing (RS) image retrieval. Existing unsupervised hashing methods usually utilize data …
PCLUDA: A pseudo-label consistency learning-based unsupervised domain adaptation method for cross-domain optical remote sensing image retrieval
D Hou, S Wang, X Tian, H **ng - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent advances in deep learning have dramatically improved the performance of content-
based remote sensing image retrieval (CBRSIR) with the same distribution of training set …
based remote sensing image retrieval (CBRSIR) with the same distribution of training set …