A multi-domain collaborative transfer learning method with multi-scale repeated attention mechanism for underwater side-scan sonar image classification
Z Cheng, G Huo, H Li - Remote Sensing, 2022 - mdpi.com
Due to the strong speckle noise caused by the seabed reverberation which makes it difficult
to extract discriminating and noiseless features of a target, recognition and classification of …
to extract discriminating and noiseless features of a target, recognition and classification of …
Feature matching and position matching between optical and SAR with local deep feature descriptor
Y Liao, Y Di, H Zhou, A Li, J Liu, M Lu… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Image matching between the optical and synthetic aperture radar (SAR) is one of the most
fundamental problems for earth observation. In recent years, many researchers have used …
fundamental problems for earth observation. In recent years, many researchers have used …
MIVI: Multi-stage feature matching for infrared and visible image
Y Di, Y Liao, K Zhu, H Zhou, Y Zhang, Q Duan, J Liu… - The Visual …, 2024 - Springer
The matching of infrared and visible images has a wide range of applications across various
fields. However, the large difference between these two types of images poses a significant …
fields. However, the large difference between these two types of images poses a significant …
A random patches based edge preserving network for land cover classification using Polarimetric Synthetic Aperture Radar images
M Imani - International Journal of Remote Sensing, 2021 - Taylor & Francis
ABSTRACT A random patches-based edge-preserving network (RPEP) is proposed for
polarimetric synthetic aperture radar (PolSAR) image classification in this paper. An initial …
polarimetric synthetic aperture radar (PolSAR) image classification in this paper. An initial …
Robust SAR Automatic Target Recognition Based on Transferred MS‐CNN with L2‐Regularization
Y Zhai, W Deng, Y Xu, Q Ke, J Gan… - Computational …, 2019 - Wiley Online Library
Though Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) via
Convolutional Neural Networks (CNNs) has made huge progress toward deep learning …
Convolutional Neural Networks (CNNs) has made huge progress toward deep learning …
Detection of damaged buildings using temporal SAR data with different observation modes
M Kim, SE Park, SJ Lee - Remote Sensing, 2023 - mdpi.com
Synthetic Aperture Radar (SAR) remote sensing has been widely used as one of the most
effective tools for responding to earthquake disasters. In general, damaged-building …
effective tools for responding to earthquake disasters. In general, damaged-building …
[HTML][HTML] Robust multi-view UAV SAR image registration based on selective correlation of log gradient descriptor
X Xiong, G Jin, Q Xu, X Liu, Q Shi - International Journal of Applied Earth …, 2024 - Elsevier
Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) image characteristics, such
as large geometric distortions, striped inhomogeneous radiation, severe speckle noise and …
as large geometric distortions, striped inhomogeneous radiation, severe speckle noise and …
Exploring Reinforced Class Separability and Discriminative Representations for SAR Target Open Set Recognition
F Gao, X Luo, R Lang, J Wang… - Remote …, 2024 - napier-repository.worktribe.com
Current synthetic aperture radar (SAR) automatic target recognition (ATR) algorithms
primarily operate under the closed-set assumption, implying that all target classes have …
primarily operate under the closed-set assumption, implying that all target classes have …
MFFA-SARNET: Deep transferred multi-level feature fusion attention network with dual optimized loss for small-sample SAR ATR
Y Zhai, W Deng, T Lan, B Sun, Z Ying, J Gan, C Mai… - Remote Sensing, 2020 - mdpi.com
Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR), most algorithms of
which have employed and relied on sufficient training samples to receive a strong …
which have employed and relied on sufficient training samples to receive a strong …
A Novel Deep Learning-Based Approach for Rift and Iceberg Recognition From ICESat-2 Data
The knowledge of rifts and icebergs in Antarctica is imperative for understanding drivers and
mechanisms controlling ice-shelf retreat. The description of their 3-D structural features has …
mechanisms controlling ice-shelf retreat. The description of their 3-D structural features has …