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Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3253627
Abstract: Over the past few years, deep learning has been introduced to tackle hyperspectral image (HSI) classification and demonstrated good performance. In particular, the convolutional neural network (CNN) based methods have progressed. However, due to the…
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Keywords:
residual spatial;
spectral attention;
attention;
proximity feature ... See more keywords
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1
Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3202866
Abstract: Hyperspectral (HS) pansharpening aims at fusing a low-resolution HS image with a high-resolution panchromatic (PAN) image to obtain a HS image with both higher spectral and spatial resolutions. However, existing HS pansharpening algorithms are mainly…
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Keywords:
shallow fusion;
network;
hyperspectral pansharpening;
deep shallow ... See more keywords
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1
Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3141870
Abstract: Hyperspectral image (HSI) classification is a hot topic in the field of remote sensing, and convolutional neural networks (CNNs) have shown good classification performance because of their capabilities of feature extraction. However, traditional CNN-based methods…
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Keywords:
hyperspectral image;
classification;
convolutional neural;
spectral attention ... See more keywords
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0
Published in 2021 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2020.3005431
Abstract: In recent years, with the development of deep learning (DL), the hyperspectral image (HSI) classification methods based on DL have shown superior performance. Although these DL-based methods have great successes, there is still room to…
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Keywords:
octave convolution;
spatial spectral;
spectral attention;
information ... See more keywords
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2
Published in 2023 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2023.3255233
Abstract: In brain-computer interface (BCI) work, how correctly identifying various features and their corresponding actions from complex Electroencephalography (EEG) signals is a challenging technology. However, most current methods do not consider EEG feature information in spatial,…
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Keywords:
temporal spectral;
eeg channel;
eeg;
spectral attention ... See more keywords