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   Articles with "segmentation remote" as a keyword



Improved gated recurrent units together with fusion for semantic segmentation of remote sensing images based on parallel hybrid network

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recommendations! Published in 2025 at "Multimedia Systems"

DOI: 10.1007/s00530-024-01654-9

Abstract: Transformer together with convolutional neural network for semantic segmentation of remote sensing images has achieved better performance than the pure module-based methods. However, the advantages of both encoding styles are not well considered, and the… read more here.

Keywords: segmentation; remote sensing; segmentation remote; semantic segmentation ... See more keywords

A New Multi-Channel Deep Convolutional Neural Network for Semantic Segmentation of Remote Sensing Image

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recommendations! 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… read more here.

Keywords: neural network; segmentation remote; semantic segmentation; image ... See more keywords

Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing Imagery

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recommendations! Published in 2024 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2025.3557362

Abstract: Vision Transformers (ViTs) have recently brought a new wave of research in the field of computer vision. These models have done particularly well in the field of image classification and segmentation. Research on semantic and… read more here.

Keywords: comparison; segmentation; segmentation remote; semantic segmentation ... See more keywords

MSCSCNet: Multiscale Convolution Selective Context Network With Boundary Supervision for Semantic Segmentation of Remote Sensing Images

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recommendations! Published in 2025 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"

DOI: 10.1109/jstars.2025.3613049

Abstract: Semantic segmentation of remote sensing images remains a challenging task due to the presence of small and indistinct objects, as well as semantic ambiguities arising from occlusions and similar visual appearances. Furthermore, the downsampling operations… read more here.

Keywords: selective context; segmentation; remote sensing; segmentation remote ... See more keywords

Semisupervised Multiscale Generative Adversarial Network for Semantic Segmentation of Remote Sensing Image

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recommendations! 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… read more here.

Keywords: remote sensing; segmentation remote; segmentation; semisupervised multiscale ... See more keywords
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Progressive Guidance Edge Perception Network for Semantic Segmentation of Remote-Sensing Images

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recommendations! 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… read more here.

Keywords: remote sensing; segmentation remote; semantic segmentation; guidance ... See more keywords

Semantic Segmentation of Remote Sensing Images With Self-Supervised Semantic-Aware Inpainting

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recommendations! 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,… read more here.

Keywords: self supervised; remote sensing; segmentation remote; semantic segmentation ... See more keywords

Historical Information-Guided Class-Incremental Semantic Segmentation in Remote Sensing Images

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recommendations! 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… read more here.

Keywords: remote sensing; segmentation remote; segmentation; historical information ... See more keywords

A Synergistical Attention Model for Semantic Segmentation of Remote Sensing Images

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recommendations! 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… read more here.

Keywords: remote sensing; segmentation remote; sensing images; attention ... See more keywords

Insight Any Instance: Promptable Instance Segmentation for Remote Sensing Images

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recommendations! Published in 2024 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2025.3543636

Abstract: Instance segmentation of remote sensing images (RSIs) is an essential task for a wide range of applications such as land planning and intelligent transport. Instance segmentation of RSIs is constantly plagued by the unbalanced ratio… read more here.

Keywords: instance segmentation; instance; remote sensing; segmentation remote ... See more keywords

RL-ISegNet: Refining Instance Segmentation for Remote Sensing Imagery via Iterative Reward Maximization With Limited Samples

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recommendations! Published in 2025 at "IEEE Transactions on Geoscience and Remote Sensing"

DOI: 10.1109/tgrs.2025.3598943

Abstract: Instance segmentation of remote sensing imagery (RSI) is vital for applications like geographic information system (GIS) updates and urban planning. Due to RSI’s diversity (e.g., scale variations and complex object shapes), instance segmentation models require… read more here.

Keywords: instance segmentation; segmentation; remote sensing; segmentation remote ... See more keywords