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[HTML][HTML] Sea ice extraction via remote sensing imagery: algorithms, datasets, applications and challenges
W Huang, A Yu, Q Xu, Q Sun, W Guo, S Ji, B Wen… - Remote Sensing, 2024 - mdpi.com
Deep learning, which is a dominating technique in artificial intelligence, has completely
changed image understanding over the past decade. As a consequence, the sea ice …
changed image understanding over the past decade. As a consequence, the sea ice …
Sea ice extraction via remote sensed imagery: Algorithms, datasets, applications and challenges
A Yu, W Huang, Q Xu, Q Sun, W Guo, S Ji… - ar** on synthetic aperture radar (SAR) imagery is important for various
purposes, including ship navigation and usage in environmental and climatological studies …
purposes, including ship navigation and usage in environmental and climatological studies …
Uncertainty-incorporated ice and open water detection on dual-polarized SAR sea ice imagery
Algorithms designed for ice–water classification of synthetic aperture radar (SAR) sea ice
imagery produce only binary (ice and water) output typically using manually labeled …
imagery produce only binary (ice and water) output typically using manually labeled …
[HTML][HTML] Lake ice-water classification of RADARSAT-2 images by integrating IRGS Segmentation with pixel-based random forest labeling
Changes to ice cover on lakes throughout the northern landscape has been established as
an indicator of climate change and variability, expected to have implications for both human …
an indicator of climate change and variability, expected to have implications for both human …
Deep semisupervised teacher–student model based on label propagation for sea ice classification
In this article, we propose a novelteacher–student-based label propagation deep
semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 …
semisupervised learning (TSLP-SSL) method for sea ice classification based on Sentinel-1 …
A novel active semisupervised convolutional neural network algorithm for SAR image recognition
F Gao, Z Yue, J Wang, J Sun, E Yang… - Computational …, 2017 - Wiley Online Library
Convolutional neural network (CNN) can be applied in synthetic aperture radar (SAR) object
recognition for achieving good performance. However, it requires a large number of the …
recognition for achieving good performance. However, it requires a large number of the …
[HTML][HTML] SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Automated sea ice charting from synthetic aperture radar (SAR) has been researched for
more than a decade, and we are still not close to unlocking the full potential of automated …
more than a decade, and we are still not close to unlocking the full potential of automated …
Semiautomated segmentation of Sentinel-1 SAR imagery for map** sea ice in Labrador coast
This study aims at proposing a semiautomated sea ice segmentation workflow utilizing
Sentinel-1 synthetic aperture radar imagery. The workflow consists of two main steps. First …
Sentinel-1 synthetic aperture radar imagery. The workflow consists of two main steps. First …
IceGCN: An Interactive Sea Ice Classification Pipeline for SAR Imagery Based on Graph Convolutional Network
Monitoring sea ice in the Arctic region is crucial for polar maritime activities. The Canadian
Ice Service (CIS) wants to augment its manual interpretation with machine learning-based …
Ice Service (CIS) wants to augment its manual interpretation with machine learning-based …