Results 21 to 30 of about 2,105 (150)
Swin Transformer Assisted Prior Attention Network for Medical Image Segmentation
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 +1 more source
Convolutional neural networks have long dominated semantic segmentation of very-high-resolution (VHR) remote sensing (RS) images. However, restricted by the fixed receptive field of convolution operation, convolution-based models cannot directly obtain ...
Yufen Xu, Shangbo Zhou, Yuhui Huang
doaj +1 more source
Asymmetric convolution Swin transformer for medical image super-resolution
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 +1 more source
A Swin transformer and MLP based method for identifying cherry ripeness and decay
Cherries are a nutritionally beneficial and economically significant crop, with fruit ripeness and decay (rot or rupture) being critical indicators in the cherry sorting process.
Ke Song, Jiwen Yang, Guohui Wang
doaj +1 more source
Swin-Pose: Swin Transformer Based Human Pose Estimation
Convolutional neural networks (CNNs) have been widely utilized in many computer vision tasks. However, CNNs have a fixed reception field and lack the ability of long-range perception, which is crucial to human pose estimation. Due to its capability to capture long-range dependencies between pixels, transformer architecture has been adopted to computer ...
Zinan Xiong +4 more
openaire +3 more sources
Gaze Estimation Based on Convolutional Structure and Sliding Window-Based Attention Mechanism
The direction of human gaze is an important indicator of human behavior, reflecting the level of attention and cognitive state towards various visual stimuli in the environment.
Yujie Li +4 more
doaj +1 more source
Sq-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
Enzymatic browning is a major quality defect of packaged “ready-to-eat” fresh-cut lettuce salads. While there have been many research and breeding efforts to counter this problem, progress is hindered by the lack of a technology to identify and quantify browning rapidly, objectively, and reliably. Here, we report a deep learning model for
Dayang Wang +4 more
openaire +3 more sources
SwiFT: Swin 4D fMRI Transformer
Modeling spatiotemporal brain dynamics from high-dimensional data, such as functional Magnetic Resonance Imaging (fMRI), is a formidable task in neuroscience. Existing approaches for fMRI analysis utilize hand-crafted features, but the process of feature extraction risks losing essential information in fMRI scans.
Peter Yongho Kim +8 more
openaire +4 more sources
Facial Expression Recognition with Swin Transformer
The task of recognizing human facial expressions plays a vital role in various human-related systems, including health care and medical fields. With the recent success of deep learning and the accessibility of a large amount of annotated data, facial expression recognition research has been mature enough to be utilized in real-world scenarios with ...
Jun-Hwa Kim, Namho Kim, Chee Sun Won
openaire +2 more sources
Face-based age estimation using improved Swin Transformer with attention-based convolution
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 +1 more source

