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Article
Remote Sensing
Shoukuan Miao et al.
Summary: In the application of remote sensing, cloud blocking poses challenges to the analysis of surface and atmospheric parameters. Existing deep learning methods struggle to accurately segment the edge information of clouds and cloud shadows. To address these issues, a multilevel feature enhanced network is proposed for cloud/shadow segmentation. Experimental results demonstrate the superiority of this method over existing approaches.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Remote Sensing
Kai Pang et al.
Summary: Designing a lightweight and robust real-time land cover segmentation algorithm is crucial for land resource applications. The existing lightweight CNN models have limitations in terms of segmentation accuracy and generalization ability. To address this issue, this paper proposes a Semantics Guided Bottleneck Network (SGBNet) that achieves a better balance between accuracy and reasoning speed. Results of comparative experiments demonstrate that the proposed method outperforms existing models in terms of segmentation accuracy while achieving lightweight.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Computer Science, Artificial Intelligence
Chen Lu et al.
Summary: Cloud and cloud shadow detection is a crucial issue in remote sensing image processing. Traditional methods are easily affected by interference and noise, and have rough segmentation results for cloud and cloud shadow boundaries. In order to address these problems, a Multi-scale Strip Pooling Feature Aggregation Network is proposed, which uses a residual network to extract different levels of semantic information. Improved Pyramid Pooling and Mutual Fusion modules are introduced to enhance multi-scale information extraction and fusion capabilities, and a Strip Boundary Refinement module is used to repair the boundary information.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Min Xia et al.
Summary: A novel multi-scale folded attention graph convolution network (MFAGCN) is proposed for parameter identification in power transmission system. This network can handle non-Euclidean data, avoid decline in identification accuracy, and achieve simultaneous identification of multiple branches and parameters through a multi-task module.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Environmental Sciences
Jiahong Gao et al.
Summary: The use of remote sensing images for land cover analysis has great potential. To improve accuracy, a multichannel feature fusion lozenge network is proposed, which utilizes three branches for feature sampling, contextual information, and feature integration, resulting in significantly improved accuracy.
JOURNAL OF APPLIED REMOTE SENSING
(2022)
Article
Engineering, Electrical & Electronic
Zhiwei Wang et al.
Summary: Parameter Identification is important in electric power transmission systems. Existing approaches have limitations in considering development trend of historical data and power grid topology constraints. This work proposes a multi-task graph convolutional neural network (MT-GCN) using GCN and FCN as building blocks, which significantly improves accuracy and robustness in real power transmission systems.
IEEE TRANSACTIONS ON POWER DELIVERY
(2022)
Article
Remote Sensing
Bingyu Chen et al.
Summary: With the improvement of segmentation effect, some studies have been applied to high-resolution remote sensing images. Existing algorithms are limited by short-range context and cannot recover high-resolution details. This paper proposes a multi-level aggregation network (MANet) to optimize the segmentation results by using a global dependency module and a two-path feature refining module.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Geochemistry & Geophysics
Chen Lu et al.
Summary: This paper proposes a dual-branch model composed of transformer and convolution network for cloud and cloud shadow segmentation in remote sensing images. By introducing a mutual guidance module, the model improves feature extraction and repairs rough segmentation boundaries in the decoding part, demonstrating its effectiveness and superiority compared to existing methods.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Environmental Sciences
Min Xia et al.
Journal of Applied Remote Sensing
(2021)
Article
Computer Science, Interdisciplinary Applications
Yi Qu et al.
Summary: A new method for automatic segmentation of clouds and their shadows in remote sensing images is proposed, using a strip pooling residual network to obtain more accurate local position information and improving segmentation accuracy by combining channel attention and spatial attention.
COMPUTERS & GEOSCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Changqian Yu et al.
Summary: Separating low-level details and high-level semantics is key to achieving high accuracy and efficiency in real-time semantic segmentation. The proposed architecture, called Bilateral Segmentation Network (BiSeNet V2), effectively handles feature representations through detail and semantics branches, striking a balance between speed and accuracy to outperform existing methods.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2021)
Article
Engineering, Electrical & Electronic
Yanan Du et al.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2019)
Article
Computer Science, Artificial Intelligence
Vijay Badrinarayanan et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2017)
Article
Environmental Sciences
Huabing Huang et al.
REMOTE SENSING OF ENVIRONMENT
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Gao Huang et al.
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Francois Chollet
30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Qi Ye et al.
COMPUTER VISION - ECCV 2016, PT VIII
(2016)
Article
Geochemistry & Geophysics
Anil M. Cheriyadat
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2014)
Review
Remote Sensing
Miao Li et al.
EUROPEAN JOURNAL OF REMOTE SENSING
(2014)
Article
Acoustics
Abdel-rahman Mohamed et al.
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
(2012)
