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Hypergraph Convolution Network Classification for Hyperspectral and LiDAR Data [PDF]
SensorsConventional remote sensing classification approaches based on single-source data exhibit inherent limitations, driving significant research interest in improved multimodal data fusion techniques.
Lei Wang, Shiwen Deng
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Remote Sensing, 2023 Superpixel-based classification using Active Learning (AL) has shown great potential in high spatial resolution remote sensing image classification tasks.
Jiechen Tang +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Each of the three satellites constituting the RADARSAT Constellation Mission (RCM) provides compact polarimetric synthetic aperture radar (CP SAR) data.
Mohsen Ghanbari +2 more
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Semantic-Aware Region Loss for Land-Cover Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Integrating superpixel segmentation into convolutional neural networks is known to be effective in enhancing the accuracy of land-cover classification.
Xianwei Zheng +5 more
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Heterogeneous Images Change Detection Based on Iterative Joint Global–Local Translation
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Most heterogeneous change detection methods based on transfer learning may not yield satisfactory results due to the lack of comprehensive utilization of the global and local characteristics of the image.
Hao Chen, Fachuan He, Jinming Liu
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A Superpixel Boundary Optimization (SBO) Framework Based on Information Measure Function
IEEE Access, 2020 Superpixel is an essential tool for computer vision. In practice, classic superpixel algorithms do not exhibit good boundary adherence with fewer superpixels, which will greatly hamper further analysis.
Guoqi Liu +3 more
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Superpixel segmentation based on image density
Systems Science & Control Engineering, 2023 Superpixel segmentation can get the middle features in image processing, effectively reduce the dimensionality of the image, and is widely used in image processing fields. To get the regular and compact superpixels in real-time, a superpixel segmentation
Dong-Fang Qiu +3 more
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Semantic Segmentation for SAR Image Based on Texture Complexity Analysis and Key Superpixels
Remote Sensing, 2020 In recent years, regional algorithms have shown great potential in the field of synthetic aperture radar (SAR) image segmentation. However, SAR images have a variety of landforms and a landform with complex texture is difficult to be divided as a whole ...
Ronghua Shang +5 more
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Extended set of superpixel features
Компьютерная оптика, 2021 Superpixel-based image processing and analysis methods usually use a small set of superpixel features. Expanding the description of superpixels can improve the quality of processing algorithms. In the paper, a set of 25 basic superpixel features of shape,
A.A. Egorova, V.V. Sergeyev
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Fuzzy Superpixels Based Semi-Supervised Similarity-Constrained CNN for PolSAR Image Classification
Remote Sensing, 2020 Recently, deep learning has been highly successful in image classification. Labeling the PolSAR data, however, is time-consuming and laborious and in response semi-supervised deep learning has been increasingly investigated in PolSAR image classification.
Yuwei Guo +5 more
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