Results 61 to 70 of about 7,104 (161)

Swin-FER: Swin Transformer for Facial Expression Recognition

Applied Sciences
The ability of transformers to capture global context information is highly beneficial for recognizing subtle differences in facial expressions. However, compared to convolutional neural networks, transformers require the computation of dependencies between each element and all other elements, leading to high computational complexity. Additionally, the
Mei Bie, Huan Xu, Yan Gao, Kai Song, Xiangjiu Che   +4 more
openaire   +2 more sources

Swin-HViT for accurate crop disease prediction using an adaptive hybrid transformer model

Discover Artificial Intelligence
Agriculture plays a pivotal role in global economic growth, yet it faces significant challenges from pests and crop diseases. Early detection is crucial for preventing large-scale crop losses and ensuring food security.
Hemalatha Gunasekaran, N. R. Wilfred Blessing, Naveen Vijayakumar Watson, B. Hariharan, Angelin Gladys Jesudoss, C. G. Anupama   +5 more
doaj   +1 more source

Improving Benign and Malignant Classifications in Mammography with ROI-Stratified Deep Learning

Bioengineering
Deep learning has achieved widespread adoption for medical image diagnosis, with extensive research dedicated to mammographic image analysis for breast cancer screening.
Kenji Yoshitsugu, Kazumasa Kishimoto, Tadamasa Takemura   +2 more
doaj   +1 more source

Classifying Deepfakes Using Swin Transformers

CoRR
3 ...
Aprille J. Xi, Eason Chen
openaire   +2 more sources

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

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   +1 more source

FML-Swin: An Improved Swin Transformer Segmentor for Remote Sensing Images

IEEE Access
Semantic segmentation of urban remote sensing images is a very challenging task. Due to the complex background, occlusion overlap and small scale target of urban remote sensing image, the semantic segmentation results have some defects such as target confusion and similarity, target boundary ambiguity, and small scale target omission.
Tianren Wu, Wenqin Deng, Rui Lin, Junzhe Jiang 0004, Xueyun Chen   +4 more
openaire   +2 more sources

Frequency Domain and Gradient-Spatial Multi-Scale Swin KANsformer for Remote Sensing Scene Classification

Remote Sensing
Transformer-based deep learning techniques have recently shown outstanding potential in remote sensing scene classification (RSSC), benefiting from their ability to capture global semantic relationships and contextual dependencies.
Xiaozhang Zhu, Junqing Huang, Haihui Wang   +2 more
doaj   +1 more source

Multi-scale capsule Swin Transformer-based method for SAR image target recognition

Tongxin xuebao
A multi-scale capsule Swin Transformer network (MSCSTN) was proposed by synergizing the semantic feature encoding of capsule units with the context feature mapping of Swin Transformer. Capsule encoding and the Swin Transformer were jointly applied to SAR
HOU Yuchao, WANG Jie, LI Hongtao, HAO Yan, DUAN Xiaoqi, HUANG Kaiwen, TIAN Youliang   +6 more
doaj  

A Recognition and Classification Method for Underground Acoustic Emission Signals Based on Improved CELMD and Swin Transformer Neural Networks

Applied Sciences
To address the challenges in processing and identifying mine acoustic emission signals, as well as the inefficiency and inaccuracy issues prevalent in existing methods, an enhanced CELMD approach is adopted for preprocessing the acoustic emission signals.
Xuebin Xie, Yunpeng Yang
doaj   +1 more source

Pavement Crack Detection Based on the Improved Swin-Unet Model

Buildings
Accurate pavement surface crack detection is crucial for analyzing pavement survey data and the development of maintenance strategies. On the basis of Swin-Unet, this study develops the improved Swin-Unet (iSwin-Unet) model with the developed skip ...
Song Chen, Zhixuan Feng, Guangqing Xiao, Xilong Chen, Chuxiang Gao, Mingming Zhao, Huayang Yu   +6 more
doaj   +1 more source