[PDF][PDF] Deep unsupervised domain adaptation: A review of recent advances and perspectives

X Liu, C Yoo, F ** with adversarial learning and spatially aware self-training
E Capliez, D Ienco, R Gaetano… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Nowadays, satellite image time series (SITS) are commonly employed to derive land-cover
maps (LCM) to support decision makers in a variety of land management applications. In the …

Multi-sensor temporal unsupervised domain adaptation for land cover map** with spatial pseudo labelling and adversarial learning

E Capliez, D Ienco, R Gaetano… - … on Geoscience and …, 2023 - ieeexplore.ieee.org
With the huge variety of Earth observation satellite missions available nowadays, the
collection of multisensor remote sensing information depicting the same geographical area …

Open-set domain adaptation for scene classification using multi-adversarial learning

J Zheng, Y Wen, M Chen, S Yuan, W Li, Y Zhao… - ISPRS Journal of …, 2024 - Elsevier
Abstract Domain adaptation methods are able to transfer knowledge across different
domains, tackling multi-sensor, multi-temporal or cross-regional remote sensing scenarios …

A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture

B Victor, A Nibali, Z He - IEEE Journal of Selected Topics in …, 2024 - ieeexplore.ieee.org
Agricultural research is essential for increasing food production to meet the needs of a
rapidly growing human population. Collecting large quantities of agricultural data helps to …

Location-aware adaptive normalization: a deep learning approach for wildfire danger forecasting

MHS Eddin, R Roscher, J Gall - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Climate change is expected to intensify and increase extreme events in the weather cycle.
Since this has a significant impact on various sectors of our life, recent works are concerned …

[HTML][HTML] A source-free unsupervised domain adaptation method for cross-regional and cross-time crop map** from satellite image time series

S Mohammadi, M Belgiu, A Stein - Remote Sensing of Environment, 2024 - Elsevier
Precise and timely information about crop types plays a crucial role in various agriculture-
related applications. However, crop type map** methods often face significant challenges …