[HTML][HTML] Pixel-associated autoencoder for hyperspectral anomaly detection

P **ang, S Ali, J Zhang, SK Jung, H Zhou - International Journal of Applied …, 2024‏ - Elsevier
Autoencoders (AEs) are central to hyperspectral anomaly detection, given their impressive
efficacy. However, the current methodologies often neglect the global pixel similarity of the …

Integration of a CNN-based model and ensemble learning for detecting post-earthquake road cracks with deep features

HC Reis, V Turk, S Karacur, AM Kurt - Structures, 2024‏ - Elsevier
A safe and healthy infrastructure is essential for humanity. Maintenance and repair of roads,
which are of great importance, especially in transportation, is essential. Roads can …

[HTML][HTML] Progressive pseudo-label framework for unsupervised hyperspectral change detection

Q Li, T Mu, A Tuniyazi, Q Yang, H Dai - International Journal of Applied …, 2024‏ - Elsevier
For hyperspectral image change detection (HSI-CD) task, unsupervised learning methods
based on pseudo-labels obtained from pre-classification method are promising due to its …

M3ICNet: A cross-modal resolution preserving building damage detection method with optical and SAR remote sensing imagery and two heterogeneous image …

H Zhang, G Ma, D Wang, Y Zhang - ISPRS Journal of Photogrammetry and …, 2025‏ - Elsevier
Building damage detection based on optical and SAR remote sensing imagery can mitigate
the adverse effects of weather, climate, and nighttime imaging. However, under emergency …

[HTML][HTML] Change detection of slow-moving landslide with multi-source SBAS-InSAR and Light-U2Net

J Cai, D Ming, F Liu, X Ling, N Liu, L Zhang, L Xu… - International Journal of …, 2025‏ - Elsevier
Abstract Interferometric Synthetic Aperture Radar (InSAR) techniques are commonly used
approach for identifying Slow-moving Landslide (SML). However, most SML boundary …

[HTML][HTML] A Novel Shipyard Production State Monitoring Method Based on Satellite Remote Sensing Images

W Qin, Y Song, H Zhu, X Yu, Y Tu - Remote Sensing, 2023‏ - mdpi.com
Monitoring the shipyard production state is of great significance to shipbuilding industry
development and coastal resource utilization. In this article, it is the first time that satellite …

Advanced Air Quality Forecasting Using an Enhanced Temporal Attention-Driven Graph Convolutional Long Short-Term Memory Model with Seasonal-Trend …

Y Boddu, A Manimaran, B Arunkumar… - IEEE …, 2024‏ - ieeexplore.ieee.org
This study presents the Improved Residual Spatial Attention-Temporal Convolutional
Network (IRSA-TCN), an advanced framework for enhancing air quality forecasting across …

TE23D: A Dataset for Earthquake Damage Assessment and Evaluation

C Ekkazan, ME Karslıgil - IEEE Journal of Selected Topics in …, 2025‏ - ieeexplore.ieee.org
Natural disasters, especially earthquakes, require rapid and accurate damage assessment
for effective response and recovery strategies. In this paper, TE23D (Turkey Earthquakes of …

[HTML][HTML] Improved early detection of wheat stripe rust through integration pigments and pigment-related spectral indices quantified from UAV hyperspectral imagery

A Guo, W Huang, B Qian, K Wang, H Liu… - International Journal of …, 2024‏ - Elsevier
Wheat stripe rust is a significant disease affecting wheat growth, often referred to as the
“cancer of wheat”. Early and accurate detection of stripe rust is crucial for enabling crop …

Structural damage detection via hierarchical damage information with volumetric assessment

IO Agyemang, J Chen, L Zeng, I Adjei-Mensah… - arxiv preprint arxiv …, 2024‏ - arxiv.org
Image environments and noisy labels hinder deep learning-based inference models in
structural damage detection. Post-detection, there is the challenge of reliance on manual …