MFFENet and ADANet: a robust deep transfer learning method and its application in high precision and fast cross-scene recognition of earthquake-induced landslides

Q Xu, C Ouyang, T Jiang, X Yuan, X Fan, D Cheng - Landslides, 2022 - Springer
Automatic recognition and segmentation methods have become an essential requirement in
identifying large-scale earthquake-induced landslides. This used to be conducted through …

Knowledge evolution learning: A cost-free weakly supervised semantic segmentation framework for high-resolution land cover classification

H Cui, G Zhang, Y Chen, X Li, S Hou, H Li, X Ma… - ISPRS Journal of …, 2024 - Elsevier
Despite the success of deep learning in land cover classification, high-resolution (HR) land
cover map** remains challenging due to the time-consuming and labor-intensive process …

Category-level selective dual-adversarial network using significance-augmented unsupervised domain adaptation for surface defect detection

S Zhang, L Su, J Gu, K Li, W Wu, M Pecht - Expert Systems with …, 2024 - Elsevier
Surface defect detection is very important to ensure the quality of industrial products.
Traditional machine learning cannot be well extended to a non-identically distributed …

A Systematic Literature Review and Bibliometric Analysis of Semantic Segmentation Models in Land Cover Map**

S Ajibola, P Cabral - Remote Sensing, 2024 - mdpi.com
Recent advancements in deep learning have spurred the development of numerous novel
semantic segmentation models for land cover map**, showcasing exceptional …

STVAE: Skip connection driven two-stream property Fusion Variational AutoEncoder for cross-region wastewater treatment plant semantic segmentation

Y Li, Y Zhang, S Randhawa, C Yang, A Zipf - Information Fusion, 2025 - Elsevier
Wastewater treatment plant (WWTP) plays a crucial role in achieving social sustainable
development goals. Precise information on WWTPs obtained through advanced semantic …

Unsupervised domain adaptation for the semantic segmentation of remote sensing images via one-shot image-to-image translation

SF Ismael, K Kayabol, E Aptoula - IEEE Geoscience and …, 2023 - ieeexplore.ieee.org
Domain adaptation is one of the prominent strategies for handling both the scarcity of pixel-
level ground truth and the domain shift, that is widely encountered in large-scale land …

High-resolution semantically consistent image-to-image translation

M Sokolov, C Henry, J Storie, C Storie… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Deep learning has become one of remote sensing scientists' most efficient computer vision
tools in recent years. However, the lack of training labels for the remote sensing datasets …

Unsupervised domain adaptation for the semantic segmentation of remote sensing images via a class-aware Fourier transform and a fine-grained discriminator

SF Ismael, K Kayabol, E Aptoula - Digital Signal Processing, 2024 - Elsevier
The semantic segmentation of remote sensing images is vital for Earth observation
purposes. However, its performance can decline significantly due to differences in dataset …

The Review of Land Use/Land Cover Map** AI Methodology and Application in the Era of Remote Sensing Big Data.

X ZHANG, Q SHI, Y SUN… - Journal of Geodesy & …, 2024 - search.ebscohost.com
With the increasing number of remote sensing satellites, the diversification of observation
modals, and the continuous advancement of artificial intelligence algorithms, historically …

A Review and Meta-analysis of Semantic Segmentation Models in Land Use/Land Cover Map**

S Ajibola, P Cabral - 2024 - preprints.org
Recent advancements in deep learning have spurred the development of numerous novel
semantic segmentation models for land cover map**, showcasing exceptional …