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DASNet: Dual attentive fully convolutional siamese networks for change detection of high resolution satellite images

7 Mar 2020lehaifeng/DASNet

However, the available methods focus mainly on the difference information between multitemporal remote sensing images and lack robustness to pseudo-change information.

CHANGE DETECTION FOR REMOTE SENSING IMAGES

End-to-End Change Detection for High Resolution Satellite Images Using Improved UNet++

10 Jun 2019daifeng2016/End-to-end-CD-for-VHR-satellite-image

To address the above-mentioned issues, a novel end-to-end CD method is proposed based on an effective encoder-decoder architecture for semantic segmentation named UNet++, where change maps could be learned from scratch using available annotated datasets.

CHANGE DETECTION FOR REMOTE SENSING IMAGES SEMANTIC SEGMENTATION

SNUNet-CD: A Densely Connected Siamese Network for Change Detection of VHR Images

17 Feb 2021likyoo/Siam-NestedUNet

Recent change detection methods always focus on the extraction of deep change semantic feature, but ignore the importance of shallow-layer information containing high-resolution and fine-grained features, this often leads to the uncertainty of the pixels at the edge of the changed target and the determination miss of small targets.

CHANGE DETECTION FOR REMOTE SENSING IMAGES

Siamese NestedUNet Networks for Change Detection of High Resolution Satellite Image

27 Oct 2020likyoo/Siam-NestedUNet

In this paper, we improve the semantic segmentation network UNet++ and propose a fully convolutional siamese network (Siam-NestedUNet) for change detection.

CHANGE DETECTION FOR REMOTE SENSING IMAGES SEMANTIC SEGMENTATION

Lake Ice Detection from Sentinel-1 SAR with Deep Learning

17 Feb 2020czarmanu/sentinel_lakeice

Lake ice, as part of the Essential Climate Variable (ECV) lakes, is an important indicator to monitor climate change and global warming.

CHANGE DETECTION FOR REMOTE SENSING IMAGES LAKE ICE MONITORING SEMANTIC SEGMENTATION SENTINEL-1 SAR PROCESSING

Lake Ice Monitoring with Webcams and Crowd-Sourced Images

18 Feb 2020czarmanu/deeplab-lakeice-webcams

On average, it achieves intersection-over-union (IoU) values of ~71% across different cameras and ~69% across different winters, greatly outperforming prior work.

CHANGE DETECTION FOR REMOTE SENSING IMAGES LAKE DETECTION LAKE ICE MONITORING SEMANTIC SEGMENTATION WEBCAM (RGB) IMAGE CLASSIFICATION

Photi-LakeIce Dataset

ISPRS Congress 2020 czarmanu/photi-lakeice-dataset

On average, it achieves intersection-over-union (IoU) values of ~71% across different cameras and ~69% across different winters, greatly outperforming prior work.

CHANGE DETECTION FOR REMOTE SENSING IMAGES LAKE DETECTION LAKE ICE MONITORING SEMANTIC SEGMENTATION WEBCAM (RGB) IMAGE CLASSIFICATION