Convolutional Transformer-Based Few-Shot Learning for Cross-Domain Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2023.3234302
Abstract: In cross-domain hyperspectral image (HSI) classification, the labeled samples of the target domain are very limited, and it is a worthy attention to obtain sufficient class information from the source domain to categorize the target… read more here.
Keywords: convolutional transformer; cross domain; domain; shot learning ... See more keywords
Convolutional Transformer Network for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3169815
Abstract: Convolutional neural networks (CNNs) have attained remarkable performance in hyperspectral image (HSI) classification. However, the existing CNNs are restricted by their limited receptive field in HSI classification. Recently, transformer networks have proved to be promising… read more here.
Keywords: convolutional transformer; classification; hsi classification; transformer network ... See more keywords
Global in Local: A Convolutional Transformer for SAR ATR FSL
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3183467
Abstract: Convolutional neural networks (CNNs) have dominated the synthetic aperture radar (SAR) automatic target recognition (ATR) for years. However, under limited SAR images, the width and depth of the CNN-based models are limited, and the widening… read more here.
Keywords: sar atr; atr fsl; convolutional transformer; sar ... See more keywords
Global–Local 3-D Convolutional Transformer Network for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3272885
Abstract: Benefiting from powerful feature extraction capabilities, convolutional neural networks (CNNs) have gained prominence in hyperspectral image (HSI) classification. Nevertheless, with restricted receptive fields of convolution kernels, CNN-based methods fail to learn complex characteristics of long-range… read more here.
Keywords: convolutional transformer; spectral spatial; local convolutional; global local ... See more keywords
EEG Conformer: Convolutional Transformer for EEG Decoding and Visualization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2022.3230250
Abstract: Due to the limited perceptual field, convolutional neural networks (CNN) only extract local temporal features and may fail to capture long-term dependencies for EEG decoding. In this paper, we propose a compact Convolutional Transformer, named… read more here.
Keywords: visualization; eeg conformer; eeg decoding; convolutional transformer ... See more keywords
A Computer-Aided Diagnostic System to Identify Diabetic Retinopathy, Utilizing a Modified Compact Convolutional Transformer and Low-Resolution Images to Reduce Computation Time
Sign Up to like & getrecommendations! Published in 2023 at "Biomedicines"
DOI: 10.3390/biomedicines11061566
Abstract: Diabetic retinopathy (DR) is the foremost cause of blindness in people with diabetes worldwide, and early diagnosis is essential for effective treatment. Unfortunately, the present DR screening method requires the skill of ophthalmologists and is… read more here.
Keywords: time; convolutional transformer; compact convolutional; model ... See more keywords