STHarDNet: Swin Transformer with HarDNet for MRI Segmentation
Applied Sciences, 2022 In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–decoder model ...
Yeonghyeon Gu +2 more
doaj +4 more sources
Swin Transformer Assisted Prior Attention Network for Medical Image Segmentation
Applied Sciences, 2022 Transformer complements convolutional neural network (CNN) has achieved better performance than improved CNN-based methods. Specially, Transformer is utilized to be combined with U-shaped structure, skip-connections, encoder, and even them all together ...
Zhihao Liao, Neng Fan, Kai Xu
doaj +2 more sources
Asymmetric convolution Swin transformer for medical image super-resolution
Alexandria Engineering Journal, 2023 Medical Image Super-Resolution plays a pivotal role in enhancing diagnostic accuracy. Transformer-based methods, such as Image Restoration Using Swin Transformer (SwinIR) and Swin transformer for fast Magnetic Resonance Imaging (SwinMR), have shown ...
Weijia Lu +9 more
doaj +2 more sources
Swin–MRDB: Pan-Sharpening Model Based on the Swin Transformer and Multi-Scale CNN
Applied Sciences, 2023 Pan-sharpening aims to create high-resolution spectrum images by fusing low-resolution hyperspectral (HS) images with high-resolution panchromatic (PAN) images. Inspired by the Swin transformer used in image classification tasks, this research constructs
Zifan Rong +3 more
doaj +2 more sources
Center Point Target Detection Algorithm Based on Improved Swin Transformer [PDF]
Jisuanji kexueAiming at the shortcomings of Swin Transformer in extracting local feature information and expressing features,this paper proposes a center point target detection algorithm based on improved Swin Transformer to improve its performance in target detection.
LIU Jiasen, HUANG Jun
doaj +2 more sources
Classification of Solar Radio Spectrum Based on Swin Transformer
Universe, 2022 Solar radio observation is a method used to study the Sun. It is very important for space weather early warning and solar physics research to automatically classify solar radio spectrums in real time and judge whether there is a solar radio burst. As the
Jian Chen +5 more
doaj +2 more sources
MoR–Swin: Efficient Vision Transformer Using Mixture of Recursions
Journal of ImagingVision Transformers, especially Swin Transformer, have become default backbones for various vision tasks but suffer from high memory consumption and training costs. This letter proposes MoR–Swin, a novel architecture that integrates Mixture of Recursions
Yongbao Ai +4 more
doaj +2 more sources
Classification and Model Explanation of Traditional Dwellings Based on Improved Swin Transformer
BuildingsThe extraction of features and classification of traditional dwellings plays significant roles in preserving and ensuring the sustainable development of these structures.
Shangbo Miao +3 more
doaj +2 more sources
Face-based age estimation using improved Swin Transformer with attention-based convolution [PDF]
Frontiers in Neuroscience, 2023 Recently Transformer models is new direction in the computer vision field, which is based on self multihead attention mechanism. Compared with the convolutional neural network, this Transformer uses the self-attention mechanism to capture global ...
Chaojun Shi +6 more
doaj +2 more sources
A Swin Transformer-Based Encoding Booster Integrated in U-Shaped Network for Building Extraction
Remote Sensing, 2022 Building extraction is a popular topic in remote sensing image processing. Efficient building extraction algorithms can identify and segment building areas to provide informative data for downstream tasks.
Xiao Xiao +5 more
doaj +3 more sources