Results 11 to 20 of about 18,617 (276)

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-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   +4 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

SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction

CoRR, 2022
Packaged fresh-cut lettuce is widely consumed as a major component of vegetable salad owing to its high nutrition, freshness, and convenience. However, enzymatic browning discoloration on lettuce cut edges significantly reduces product quality and shelf ...
Luo, Yaguang, Wang, Dayang, Xu, Yongshun, Yu, Hengyong, Zhang, Boce   +4 more
core   +2 more sources

Architectural Scalability and Attention Stabilization for Robust Impulsive Acoustic Spectrogram Classification Using Swin Transformer V2

IEEE Access
Impulsive acoustic event classification based on spectrogram representations remains challenging due to the non-stationary and broadband characteristics of transient signals.
Pafan Doungpaisan, Peerapol Khunarsa
doaj   +2 more sources

Detection Method of Concave Defect on Specular Surfaces Based on Swin Transformer [PDF]

Shallow concave defects on mirrored surfaces are difficult to detect automatically. This paper proposes a defect detection method using a deep neural network (DNN) that learns the presence or absence of distortion in the image of a stripe pattern ...
Tanaka, Kazumoto
core   +3 more sources

Swin Routiformer: Moss Classification Algorithm Based on Swin Transformer With Bi-Level Routing Attention [PDF]

IEEE Access
Accurate classification of moss species is essential for progress in ecology and biology. However, traditional methods for classifying moss require significant expertise, and current deep learning techniques struggle due to limited dataset diversity and ...
Peichen Li, Huiqin Wang, Zhan Wang, Ke Wang, Chong Wang   +4 more
doaj   +2 more sources

A multi-scale attention-based Swin transformer model for medical images segmentation. [PDF]

Sci Rep
Mirab Golkhatmi B, Houshmand M, Hosseini SA.   +2 more
europepmc   +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