Results 101 to 110 of about 192,101 (191)

Swin-Pose: Swin Transformer Based Human Pose Estimation

, 2022
Convolutional neural networks (CNNs) have been widely utilized in many computer vision tasks. However, CNNs have a fixed reception field and lack the ability of long-range perception, which is crucial to human pose estimation.
Wang, Chenxi, Li, Ying, Luo, Yan, Xiong, Zinan, Cao, Yu   +4 more
core  

Deep learning cone‐beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects

Journal of Periodontology, Volume 97, Issue 9, Page 1847-1859, September 2026.
Abstract Background The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone‐beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D).
Daniel Palkovics, Balint Molnar, Csaba Pinter, David García‐Mato, Andres Diaz‐Pinto, Attila Tanacs, Andrea Dobos, Peter Windisch, Christoph A. Ramseier   +8 more
wiley   +1 more source

Degenerate Swin to Win: Plain Window-based Transformer without Sophisticated Operations

, 2022
The formidable accomplishment of Transformers in natural language processing has motivated the researchers in the computer vision community to build Vision Transformers.
Li, Ping, Yu, Tan
core  

Advanced Deep Learning and Hybrid Architectures in Biomedical Data Analysis for Advances in Medicine

Medicine Advances, Volume 4, Issue 3, Page 274-286, September 2026.
This review summarizes AI methods for biomedical imaging and clinical data analysis. Deep learning and multimodal models improve feature learning and diagnostic accuracy. Future progress requires explainable and generalizable AI for precision medicine.
Lifeng Li, Ashfaque Khowaja, Yucheng Song, Mingwei Zhang, Shabir Hussain   +4 more
wiley   +1 more source

Performance Evaluation of Swin Vision Transformer Model using Gradient Accumulation Optimization Technique

, 2023
Vision Transformers (ViTs) have emerged as a promising approach for visual recognition tasks, revolutionizing the field by leveraging the power of transformer-based architectures.
Dorgham, Osama, Aburass, Sanad
core  

Machine Learning‐Based Postprocessing Ensemble of AI and NWP Models for Short‐Term Air Temperature Forecasting Over Beijing

Meteorological Applications, Volume 33, Issue 5, September/October 2026.
Integrating data‐driven weather prediction models and physics‐based NWP models via machine‐learning ensembles significantly enhances short‐term air temperature forecasts over Beijing. The XGBoost‐based ensemble reduces RMSE by over 20% relative to the simple ensemble mean baseline by effectively mitigating systematic bias and diurnal phase shifts ...
Peng He, Chenxi Jin, Yan Dong, Chen Qi, Ting Lei   +4 more
wiley   +1 more source

Speech Swin-Transformer: Exploring a Hierarchical Transformer with Shifted Windows for Speech Emotion Recognition [PDF]

Swin-Transformer has demonstrated remarkable success in computer vision by leveraging its hierarchical feature representation based on Transformer. In speech signals, emotional information is distributed across different scales of speech features, e.\,g.,
Lu, Cheng, Lian, Hailun, Zong, Yuan, Zhao, Yan, Zheng, Wenming, Wang, Yong, Schuller, Björn   +6 more
core   +1 more source

Transfer Learning With U-Swin Transformer for Adaptive Ground Roll Attenuation in Seismic Records From Sabkha Environments

IEEE Access
Ground roll is a dominant coherent noise in land seismic data, characterized by low frequency, low velocity, and high amplitude. often overlaps with reflection arrivals, thereby reducing the reliability of seismic imaging and interpretation.
Ahmed Eleslambouly, Guibin Zhao, Fateh Bouchaala, Mohammed Y. Ali, Jun Matsushima   +4 more
doaj   +1 more source

Contour‐regulated registration framework for Liver CT perfusion images

Medical Physics, Volume 53, Issue 9, September 2026.
Abstract Background Liver computed tomography perfusion (CTp) imaging enables quantitative assessment of vascular dynamics but is highly susceptible to motion‐induced artifacts arising from breath‐hold variability and involuntary patient motion. These effects cause different portions of the liver to fall within the imaging field of view across time ...
Zhan Xu, Yao Zhao, Xinru Chen, Jinyong Lin, Roya Barati, Chaan S. Ng, Jinzhong Yang   +6 more
wiley   +1 more source

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

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   +1 more source