Results 21 to 30 of about 206,029 (232)

An Efficient FPGA-Based Accelerator for Swin Transformer

CoRR, 2023
Since introduced, Swin Transformer has achieved remarkable results in the field of computer vision, it has sparked the need for dedicated hardware accelerators, specifically catering to edge computing demands. For the advantages of flexibility, low power consumption, FPGAs have been widely employed to accelerate the inference of convolutional neural ...
Zhiyang Liu, Pengyu Yin, Zhenhua Ren
openaire   +4 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, Guowu Yuan, Hao Zhou, Chengming Tan, Lei Yang, Siqi Li   +5 more
doaj   +2 more sources

Center Point Target Detection Algorithm Based on Improved Swin Transformer [PDF]

Jisuanji kexue
Aiming 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

Quantum integration in swin transformer mitigates overfitting in breast cancer screening [PDF]

Scientific Reports
To explore the potential of quantum computing in advancing transformer-based deep learning models for breast cancer screening, this study introduces the Quantum-Enhanced Swin Transformer (QEST).
Zongyu Xie, Xiaoguang Yang, Shuni Zhang, Jingru Yang, Yun Zhu, Aoqi Zhang, Haitao Sun, Qun Dai, Lei Li, Hongde Liu, Wenlong Ming, Menghan Dou   +11 more
doaj   +2 more sources

Tooth Type Enhanced Transformer for Children Caries Diagnosis on Dental Panoramic Radiographs

Diagnostics, 2023
The objective of this study was to introduce a novel deep learning technique for more accurate children caries diagnosis on dental panoramic radiographs.
Xiaojie Zhou, Guoxia Yu, Qiyue Yin, Jun Yang, Jiangyang Sun, Shengyi Lv, Qing Shi   +6 more
doaj   +1 more source

Video Swin Transformer

2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
The vision community is witnessing a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major video recognition benchmarks. These video models are all built on Transformer layers that globally connect patches across the spatial and temporal dimensions.
Ze Liu, Jia Ning, Yue Cao 0001, Yixuan Wei, Zheng Zhang 0022, Stephen Lin 0001, Han Hu 0001   +6 more
openaire   +3 more sources

Swin transformer for fast MRI

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, Yingying Fang, Yinzhe Wu 0001, Huanjun Wu, Zhifan Gao, Yang Li 0010, Javier Del Ser, Jun Xia 0002, Guang Yang 0006   +8 more
openaire   +5 more sources

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, Hirokatsu Kataoka, Kensho Hara, Ryozo Noguchi   +3 more
doaj   +1 more source

Transformer-Based Model with Dynamic Attention Pyramid Head for Semantic Segmentation of VHR Remote Sensing Imagery

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
doaj   +1 more source

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
doaj   +1 more source