Superpixel-based graph convolutional neural network for polarimetric synthetic aperture radar image classification. [PDF]
Sci RepImani M.
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Anomaly detection of hyperspectral images based on improved isolation forest algorithm. [PDF]
Sci RepLi A.
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A Graph-Based Superpixel Segmentation Approach Applied to Pansharpening. [PDF]
Sensors (Basel)Hallabia H.
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SPX-GNN: An Explainable Graph Neural Network for Harnessing Long-Range Dependencies in Tuberculosis Classifications in Chest X-Ray Images. [PDF]
Diagnostics (Basel)Pala MA, Navdar MB.
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Boundary-preserving superpixel segmentation
Journal of Applied Science and EngineeringIn recent years, superpixel segmentation has been widely used in image processing tasks as a preprocessing step. Superpixel segmentation aims to group pixels into homogeneous regions while maintaining edges. This paper proposes a superpixel segmentation algorithm based on boundary preservation.
Yuejia Lin +3 more
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Dynamic-budget superpixel active learning for semantic segmentation. [PDF]
Front Artif IntellWang Y, Stavness I.
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Deep superpixel generation and clustering for weakly supervised segmentation of brain tumors in MR images. [PDF]
BMC Med ImagingYoo JJ, Namdar K, Khalvati F.
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Multiscale superpixel depth feature extraction for hyperspectral image classification. [PDF]
Sci RepYan Q, Zhang S, Chen X, Zheng Z.
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A SPATIALLY VARYING HIERARCHICAL RANDOM EFFECTS MODEL FOR LONGITUDINAL MACULAR STRUCTURAL DATA IN GLAUCOMA PATIENTS. [PDF]
Ann Appl StatSu BE +3 more
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CNN-TumorNet: leveraging explainability in deep learning for precise brain tumor diagnosis on MRI images. [PDF]
Front OncolRasool N +7 more
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