Results 11 to 20 of about 118,760 (177)
Hyperspectral Imagery Classification Based on Multiscale Superpixel-Level Constraint Representation [PDF]
Remote Sensing, 2020 Sparse representation (SR)-based models have been widely applied for hyperspectral image classification. In our previously established constraint representation (CR) model, we exploited the underlying significance of the sparse coefficient and proposed ...
Haoyang Yu +5 more
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Dynamic PET Image Reconstruction Incorporating Multiscale Superpixel Clusters [PDF]
IEEE Access, 2021 Dynamic positron emission tomography (PET) image reconstruction is challenging due to the low-count statistics of individual frames. This study proposes a novel reconstruction framework aiming to enhance the quantitative accuracy of individual dynamic ...
Shuangliang Cao +5 more
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A Superpixel-Based Relational Auto-Encoder for Feature Extraction of Hyperspectral Images
Remote Sensing, 2019 Filter banks transferred from a pre-trained deep convolutional network exhibit significant performance in heightening the inter-class separability for hyperspectral image feature extraction, but weakening the intra-class consistency simultaneously.
Miaomiao Liang, Licheng Jiao, Zhe Meng
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Multiscale Union Regions Adaptive Sparse Representation for Hyperspectral Image Classification
Remote Sensing, 2017 Sparse Representation has been widely applied to classification of hyperspectral images (HSIs). Besides spectral information, the spatial context in HSIs also plays an important role in the classification.
Fei Tong +3 more
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International Journal of Digital Earth, 2022 In map multiscale visualization, typification is the process of replacing original objects, such as buildings, using a smaller number of objects while maintaining initial geometrical and distribution characteristics.
Yilang Shen +4 more
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Remote Sensing, 2020 In this paper, superpixel features and extended multi-attribute profiles (EMAPs) are embedded in a multiple kernel learning framework to simultaneously exploit the local and multiscale information in both spatial and spectral dimensions for hyperspectral
Lei Pan, Chengxun He, Yang Xiang, Le Sun
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingPolarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation.
Ru Wang, Yinju Nie, Jie Geng
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Clinically Deployable Handwriting Biomarkers of Parkinson's Disease via Multiscale Attention and Bayesian-Genetic Optimization. [PDF]
Brain BehavTablet‐based handwriting tasks (spiral, meander, and wave) are transformed into unified images and analyzed using PD‐MGMA‐DSCNN, a lightweight multiscale gated attention network. Bayesian–genetic optimization improves performance, while SHAP attribution maps provide interpretable handwriting biomarkers for Parkinson's disease screening.
Rezaee K, Fakhrabadi AK.
europepmc +2 more sources
Superpixel-Guided Matrix-Valued Kernel Functions for Multiscale Nonlinear Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral unmixing is a critical challenge in the analysis of hyperspectral remote sensing data. Due to the complex interactions between incident light and materials, which are significantly influenced by the three-dimensional geometry of the scene ...
Xiu Zhao, Meiping Song
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MSP : Refine Boundary Segmentation via Multiscale Superpixel
CoRR, 2021 In this paper, we propose a simple but effective message passing method to improve the boundary quality for the semantic segmentation result. Inspired by the generated sharp edges of superpixel blocks, we employ superpixel to guide the information passing within feature map.
Jie Zhu +4 more
openaire +2 more sources