Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective

MD Hossain, D Chen - ISPRS Journal of Photogrammetry and Remote …, 2019 - Elsevier
Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …

Global and local contrastive self-supervised learning for semantic segmentation of HR remote sensing images

H Li, Y Li, G Zhang, R Liu, H Huang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, supervised deep learning has achieved a great success in remote sensing image
(RSI) semantic segmentation. However, supervised learning for semantic segmentation …

Geospatial transformer is what you need for aircraft detection in SAR Imagery

L Chen, R Luo, J Xing, Z Li, Z Yuan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Although deep learning techniques have achieved noticeable success in aircraft detection,
the scale heterogeneity, position difference, complex background interference, and speckle …

Semantic segmentation in aerial imagery using multi-level contrastive learning with local consistency

M Tang, K Georgiou, H Qi… - Proceedings of the …, 2023 - openaccess.thecvf.com
Semantic segmentation in large-scale aerial images is an extremely challenging task. On
one hand, the limited ground truth, as compared to the vast area the images cover, greatly …

A fast aircraft detection method for SAR images based on efficient bidirectional path aggregated attention network

R Luo, L Chen, J Xing, Z Yuan, S Tan, X Cai, J Wang - Remote Sensing, 2021 - mdpi.com
In aircraft detection from synthetic aperture radar (SAR) images, there are several major
challenges: the shattered features of the aircraft, the size heterogeneity and the interference …

Glassboxing deep learning to enhance aircraft detection from SAR imagery

R Luo, J Xing, L Chen, Z Pan, X Cai, Z Li, J Wang… - Remote Sensing, 2021 - mdpi.com
Although deep learning has achieved great success in aircraft detection from SAR imagery,
its blackbox behavior has been criticized for low comprehensibility and interpretability. Such …

[HTML][HTML] Employing deep learning for automatic river bridge detection from SAR images based on adaptively effective feature fusion

L Chen, T Weng, J Xing, Z Li, Z Yuan, Z Pan… - International Journal of …, 2021 - Elsevier
Automatic river bridge detection is a typical and valuable application for SAR image
analysis. However, the background information of SAR image is complex, and there are …

MapReduce-based fast fuzzy c-means algorithm for large-scale underwater image segmentation

X Li, J Song, F Zhang, X Ouyang, SU Khan - Future Generation Computer …, 2016 - Elsevier
The research on underwater image segmentation has to deal with the rapid increasing
volume of images and videos. To handle this issue, parallel computing paradigms, such as …

A multi-scale deep neural network for water detection from SAR images in the mountainous areas

L Chen, P Zhang, J Xing, Z Li, X Xing, Z Yuan - Remote Sensing, 2020 - mdpi.com
Water detection from Synthetic Aperture Radar (SAR) images has been widely utilized in
various applications. However, it remains an open challenge due to the high similarity …

STransU2Net: Transformer based hybrid model for building segmentation in detailed satellite imagery

G Liu, K Diao, J Zhu, Q Wang, M Li - PloS one, 2024 - journals.plos.org
As essential components of human society, buildings serve a multitude of functions and
significance. Convolutional Neural Network (CNN) has made remarkable progress in the …