Artificial intelligence for remote sensing data analysis: A review of challenges and opportunities
Artificial intelligence (AI) plays a growing role in remote sensing (RS). Applications of AI,
particularly machine learning algorithms, range from initial image processing to high-level …
particularly machine learning algorithms, range from initial image processing to high-level …
Deep learning for SAR ship detection: Past, present and future
J Li, C Xu, H Su, L Gao, T Wang - Remote Sensing, 2022 - mdpi.com
After the revival of deep learning in computer vision in 2012, SAR ship detection comes into
the deep learning era too. The deep learning-based computer vision algorithms can work in …
the deep learning era too. The deep learning-based computer vision algorithms can work in …
HOG-ShipCLSNet: A novel deep learning network with hog feature fusion for SAR ship classification
Ship classification in synthetic aperture radar (SAR) images is a fundamental and significant
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …
step in ocean surveillance. Recently, with the rise of deep learning (DL), modern abstract …
LS-SSDD-v1. 0: A deep learning dataset dedicated to small ship detection from large-scale Sentinel-1 SAR images
Ship detection in synthetic aperture radar (SAR) images is becoming a research hotspot. In
recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR …
recent years, as the rise of artificial intelligence, deep learning has almost dominated SAR …
Balance learning for ship detection from synthetic aperture radar remote sensing imagery
Synthetic aperture radar (SAR) is playing an important role in maritime domain awareness.
As a fundamental ocean mission, SAR ship detection can offer high-quality services for …
As a fundamental ocean mission, SAR ship detection can offer high-quality services for …
A group-wise feature enhancement-and-fusion network with dual-polarization feature enrichment for SAR ship detection
Ship detection in synthetic aperture radar (SAR) images is a significant and challenging
task. However, most existing deep learning-based SAR ship detection approaches are …
task. However, most existing deep learning-based SAR ship detection approaches are …
Exploring vision transformers for polarimetric SAR image classification
H Dong, L Zhang, B Zou - IEEE Transactions on Geoscience …, 2021 - ieeexplore.ieee.org
As one of the most popular topics in polarimetric synthetic aperture radar (PolSAR)
community, PolSAR image classification has always been an important way for PolSAR …
community, PolSAR image classification has always been an important way for PolSAR …
Dualistic cascade convolutional neural network dedicated to fully PolSAR image ship detection
G Gao, Q Bai, C Zhang, L Zhang, L Yao - ISPRS Journal of …, 2023 - Elsevier
Influenced by the imaging mechanism, the occurrence of interference clutter in synthetic
aperture radar (SAR) renders the identification of false alarms using detectors challenging …
aperture radar (SAR) renders the identification of false alarms using detectors challenging …
Survey of deep learning for autonomous surface vehicles in marine environments
Within the next several years, there will be a high level of autonomous technology that will
be available for widespread use, which will reduce labor costs, increase safety, save energy …
be available for widespread use, which will reduce labor costs, increase safety, save energy …
BANet: A balance attention network for anchor-free ship detection in SAR images
Q Hu, S Hu, S Liu - IEEE Transactions on Geoscience and …, 2022 - ieeexplore.ieee.org
Recently, methods based on deep learning have been successfully applied to ship detection
for synthetic aperture radar (SAR) images. However, most current ship detection networks …
for synthetic aperture radar (SAR) images. However, most current ship detection networks …