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Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3009976
Abstract: The semantic segmentation of remote sensing (RS) image is a hot research field. With the development of deep learning, the semantic segmentation based on a full convolution neural network greatly improves the segmentation accuracy. The…
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Keywords:
neural network;
segmentation remote;
semantic segmentation;
image ... See more keywords
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Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2020.3036823
Abstract: Semantic segmentation of remote sensing images based on deep neural networks has gained wide attention recently. Although many methods have achieved amazing performance, they need large amounts of labeled images to distinguish the differences in…
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Keywords:
remote sensing;
segmentation remote;
segmentation;
semisupervised multiscale ... See more keywords
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Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3058427
Abstract: Remarkable improvements have been seen in the semantic segmentation of remote-sensing images. As an effective structure to aggregate shallow information and deep information, encoder–decoder structure has been widely used in many state-of-the-art models, but it…
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Keywords:
remote sensing;
segmentation remote;
semantic segmentation;
guidance ... See more keywords
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Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3212795
Abstract: Semantic segmentation of remote sensing imageries plays a crucial role in resource exploration, urban planning, weather forecasting, etc. For this task, deep learning-based methods have shown significant achievement, typically trained with large-scale labeled data. However,…
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Keywords:
self supervised;
remote sensing;
segmentation remote;
semantic segmentation ... See more keywords
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Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3170349
Abstract: Despite the extraordinary success of the deep architectures on semantic segmentation for remote sensing (RS) images, they have difficulties in learning new classes from a sequential data stream because of catastrophic forgetting. Continual learning for…
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Keywords:
remote sensing;
segmentation remote;
segmentation;
historical information ... See more keywords
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Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3243954
Abstract: In remotely sensed images, high intraclass variance and interclass similarity are ubiquitous due to complex scenes and objects with multivariate features, making semantic segmentation a challenging task. Deep convolutional neural networks can solve this problem…
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Keywords:
remote sensing;
segmentation remote;
sensing images;
attention ... See more keywords
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Published in 2018 at "Computer Optics"
DOI: 10.18287/2412-6179-2018-42-3-447-456
Abstract: We propose a method of segmentation of remote sensing time series data, which exploits multi-temporal information to identify objects’ boundaries. Extracting homogeneous objects with similar temporal behavior, the method analyzes large volumes of multi-temporal input…
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Keywords:
segmentation remote;
time;
time series;
remote sensing ... See more keywords