Wood species recognition through FGLAM textural and spectral feature fusion
Sign Up to like & getrecommendations! Published in 2021 at "Wood Science and Technology"
DOI: 10.1007/s00226-021-01262-0
Abstract: In this study, a method based on fuzzy gray level aura matrix (FGLAM) textural feature and spectral feature fusion is proposed to improve the accuracy of wood species classification. The experimental dataset is acquired by… read more here.
Keywords: fglam textural; wood species; fusion; feature ... See more keywords
Tetrahedral spectral feature-Based bayesian manifold learning for grey matter morphometry: Findings from the Alzheimer's disease neuroimaging initiative
Sign Up to like & getrecommendations! Published in 2021 at "Medical image analysis"
DOI: 10.1016/j.media.2021.102123
Abstract: Structural and anatomical analyses of magnetic resonance imaging (MRI) data often require a reconstruction of the three-dimensional anatomy to a statistical shape model. Our prior work demonstrated the usefulness of tetrahedral spectral features for grey… read more here.
Keywords: spectral feature; matter; grey matter; matter morphometry ... See more keywords
DSFA-PINN: Deep Spectral Feature Aggregation Physics Informed Neural Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3153056
Abstract: Solving parametric partial differential equations using artificial intelligence is taking the pace. It is primarily because conventional numerical solvers are computationally expensive and require significant time to converge a solution. However, physics informed deep learning… read more here.
Keywords: neural network; spectral feature; physics; physics informed ... See more keywords
Unsupervised Spatial–Spectral Feature Learning by 3D Convolutional Autoencoder for Hyperspectral Classification
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2019.2908756
Abstract: Feature learning technologies using convolutional neural networks (CNNs) have shown superior performance over traditional hand-crafted feature extraction algorithms. However, a large number of labeled samples are generally required for CNN to learn effective features under… read more here.
Keywords: feature extraction; spectral feature; feature learning; unsupervised spatial ... See more keywords
Style Transformation-Based Spatial–Spectral Feature Learning for Unsupervised Change Detection
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2020.3026099
Abstract: Due to the inconsistent imaging environment, the styles of multitemporal multispectral images (MSIs) are quite different, such as image brightness and transparency. For multitemporal MSIs with different styles, the “same object with different spectra” problem… read more here.
Keywords: change detection; spatial spectral; spectral feature; detection ... See more keywords
Automatic Spectral Representation With Improved Stacked Spectral Feature Space Patch (ISSFSP) for CNN-Based Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3210438
Abstract: Hyperspectral imaging (HSI) effectively supports land cover (LC) classification in understanding nature–human interactions. The LC classification quality depends heavily on the input features. Combining convolutional neural network (CNN) and stacked spectral feature space patch (SSFSP)… read more here.
Keywords: spectral feature; classification; cnn; feature space ... See more keywords
Ultralightweight Spatial–Spectral Feature Cooperation Network for Change Detection in Remote Sensing Images
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3261273
Abstract: Deep convolutional neural networks (CNNs) have achieved much success in remote sensing image change detection (CD) but still suffer from two main problems. First, the existing multiscale feature fusion methods often use redundant feature extraction… read more here.
Keywords: spatial spectral; spectral feature; remote sensing; feature cooperation ... See more keywords
Multimodal image and spectral feature learning for efficient analysis of water-suspended particles.
Sign Up to like & getrecommendations! Published in 2023 at "Optics express"
DOI: 10.1364/oe.470878
Abstract: We have developed a method to combine morphological and chemical information for the accurate identification of different particle types using optical measurement techniques that require no sample preparation. A combined holographic imaging and Raman spectroscopy… read more here.
Keywords: spectral feature; feature learning; multimodal image; image spectral ... See more keywords