Change detection methods for remote sensing in the last decade: A comprehensive review

G Cheng, Y Huang, X Li, S Lyu, Z Xu, H Zhao, Q Zhao… - Remote Sensing, 2024 - mdpi.com
Change detection is an essential and widely utilized task in remote sensing that aims to
detect and analyze changes occurring in the same geographical area over time, which has …

A systematic literature review on multimodal machine learning: Applications, challenges, gaps and future directions

A Barua, MU Ahmed, S Begum - Ieee access, 2023 - ieeexplore.ieee.org
Multimodal machine learning (MML) is a tempting multidisciplinary research area where
heterogeneous data from multiple modalities and machine learning (ML) are combined to …

Unsupervised domain adaptation augmented by mutually boosted attention for semantic segmentation of VHR remote sensing images

X Ma, X Zhang, Z Wang, MO Pun - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This work investigates unsupervised domain adaptation (UDA)-based semantic
segmentation of very high-resolution (VHR) remote sensing (RS) images from different …

A decoder-focused multitask network for semantic change detection

Z Li, X Wang, S Fang, J Zhao… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Recently, semantic change detection (SCD) has gained growing attention from the remote-
sensing (RS) research community due to its critical role in Earth observation applications …

Beyond supervised learning in remote sensing: A systematic review of deep learning approaches

B Hosseiny, M Mahdianpari, M Hemati… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
An increasing availability of remote sensing data in the era of geo big-data makes producing
well-represented, reliable training data to be more challenging and requires an excessive …