Results 1 to 10 of about 15,226 (184)

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

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   +4 more sources

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   +4 more sources

Swin transformer for fast MRI [PDF]

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 ...
Fang, Yingying, Gao, Zhifan, Huang, Jiahao, Li, Yang, Ser, Javier Del, Wu, Huanjun, Wu, Yinzhe, Xia, Jun, Yang, Guang   +8 more
core   +10 more sources

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 ...
Irsal, Riyandi Banovbi Putera, Laksono, Blessius Sheldo Putra, Pinasthika, Krisna, Shabiyya, Syifa Hukma, Yudistira, Novanto   +4 more
core   +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, Chaojun Shi, Shiwei Zhao, Ke Zhang, Ke Zhang, Yibo Wang, Longping Liang   +6 more
doaj   +3 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

SwiFT: Swin 4D fMRI Transformer

, 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
Bae, Sangyoon, Cha, Jiook, Joo, Sunghwan, Jung, Yoonho, Kim, Peter Yongho, Kwon, Junbeom, Lee, Donggyu, Moon, Taesup, Yoo, Shinjae   +8 more
core   +2 more sources

SPT-Swin: A Shifted Patch Tokenization Swin Transformer for Image Classification

IEEE Access
Recently, the transformer-based model e.g., the vision transformer (ViT) has been extensively used in computer vision tasks. The superior performance of the ViT leads to the requirement of an enormous dataset and the complexity of calculating self ...
Gazi Jannatul Ferdous, Khaleda Akhter Sathi, Md. Azad Hossain, M. Ali Akber Dewan   +3 more
doaj   +2 more sources

Residual swin transformer for classifying the types of cotton pests in complex background [PDF]

Frontiers in Plant Science
BackgroundCotton pests have a major impact on cotton quality and yield during cotton production and cultivation. With the rapid development of agricultural intelligence, the accurate classification of cotton pests is a key factor in realizing the precise
Ting Zhang, Jikui Zhu, Fengkui Zhang, Shijie Zhao, Wei Liu, Ruohong He, Hongqiang Dong, Qingqing Hong, Changwei Tan, Ping Li   +9 more
doaj   +3 more sources

Swin-transformer for weak feature matching. [PDF]

Sci Rep
Feature matching in computer vision is crucial but challenging in weakly textured scenes due to the lack of pattern repetition. We introduce the SwinMatcher feature matching method, aimed at addressing the issues of low matching quantity and poor matching precision in weakly textured scenes.
Guo Y, Li W, Zhai P.
europepmc   +3 more sources