Results 21 to 30 of about 192,101 (191)

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

Swin-HSSAM: A green coffee bean grading method by Swin transformer.

PLoS ONE
A novel shifted window (Swin) Transformer coffee bean grading model called Swin-HSSAM has been proposed to address the challenges of accurately classifying green coffee beans and low identification accuracy.
Yujie Jiao, Yuqing Zhao, Aoying Jia, Tianyun Wang, Jiashun Li, Kaiming Xiang, Hangyu Deng, Maochang He, Rui Jiang, Yue Zhang   +9 more
doaj   +2 more sources

SwiFT: Swin 4D fMRI Transformer [PDF]

, 2023
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
Lee, Dong Gyu, Yoo,Shin Jae, Moon, Tae Sup, Bae, Sang Yoon, Cha, Jiook, Jung, Yoon Ho, Kim, Peter Yongho, Joo, Sung Hwan, Kwon, Jun Beom   +8 more
core   +3 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

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

S-Swin Transformer: simplified Swin Transformer model for offline handwritten Chinese character recognition [PDF]

PeerJ Computer Science, 2022
The Transformer shows good prospects in computer vision. However, the Swin Transformer model has the disadvantage of a large number of parameters and high computational effort.
Yongping Dan, Zongnan Zhu, Weishou Jin, Zhuo Li   +3 more
doaj   +2 more sources

SparseSwin: Swin Transformer with Sparse Transformer Block [PDF]

, 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 ...
Shabiyya, Syifa Hukma, Irsal, Riyandi Banovbi Putera, Yudistira, Novanto, Laksono, Blessius Sheldo Putra, Pinasthika, Krisna   +4 more
core   +1 more source

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, Jiahui Chen, Jiaxin Ma, Xiwen Wang, Wei Zhang   +4 more
doaj   +1 more source