A New Multi-Channel Deep Convolutional Neural Network for Semantic Segmentation of Remote Sensing Image
Sign Up to like & getrecommendations! 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
Semisupervised Multiscale Generative Adversarial Network for Semantic Segmentation of Remote Sensing Image
Sign Up to like & getrecommendations! 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
Progressive Guidance Edge Perception Network for Semantic Segmentation of Remote-Sensing Images
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Sign Up to like & getrecommendations! 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
Identification of dynamically homogeneous areas with time series segmentation of remote sensing data
Sign Up to like & getrecommendations! 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… read more here.
Keywords: segmentation remote; time; time series; remote sensing ... See more keywords