Results 21 to 30 of about 7,104 (161)
Neurocomputing, 2022 Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can produce high-resolution and reproducible images. However, a long scanning time is required for high-quality MR images, which leads to exhaustion and discomfort of patients, inducing more artefacts due to voluntary movements of the patients and involuntary physiological
Jiahao Huang +8 more
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Sparseswin: Swin Transformer with Sparse Transformer Block
Neurocomputing, 2023 Advancements in computer vision research have put transformer architecture as the state of the art in computer vision tasks. One of the known drawbacks of the transformer architecture is the high number of parameters, this can lead to a more complex and inefficient algorithm.
Krisna Pinasthika +4 more
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Transformer-based ripeness segmentation for tomatoes
Smart Agricultural Technology, 2023 With the recent development of computer vision technology, various computer vision techniques have been applied to agriculture. Recently, the Transformer network has been introduced to image recognition, which allows a different approach to extracting ...
Risa Shinoda +3 more
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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
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Entropy, 2022 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
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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
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A Swin transformer and MLP based method for identifying cherry ripeness and decay
Frontiers in Physics, 2023 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
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Swin-Pose: Swin Transformer Based Human Pose Estimation
2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2022 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
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Gaze Estimation Based on Convolutional Structure and Sliding Window-Based Attention Mechanism
Sensors, 2023 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
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Sq-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
IEEE Access, 2023 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
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