Results 91 to 100 of about 7,061 (200)

Short‐Term Hourly Weather Forecasting Using PredRNN With Image Preprocessing

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract Global weather forecast models are vital tools with numerous applications, including public safety, agriculture, and transportation. Recent advancements in artificial intelligence (AI) and deep learning (DL) have shown the potential to enhance weather forecasting accuracy and speed.
Hoang Tran, Hao Li, Vinh Ngoc Tran, Tam V. Nguyen, Manh‐Hung Le, Thanh Duc Dang, Hong Xuan Do, Hung T. Pham, Tan Bui‐Thanh, L. Ruby Leung   +9 more
wiley   +1 more source

Multi‐angle, cross‐domain fusion strategy enhances automated insect identification and hierarchical categorization: a case study on assassin bugs (Hemiptera: Reduviidae)

Cladistics, Volume 42, Issue 4, Page 358-373, August 2026.
Abstract Automated insect identification systems hold significant value for biodiversity monitoring, pest management, citizen science initiatives and systematic studies, particularly in an era of declining expertise in insect taxonomy. However, current deep learning approaches often rely on standardized specimen photos from limited‐angles and ...
Xinkai Wang, Huaiyu Liu, Zhuo Chen, Yisheng Zhao, Yingqi Liu, Haoyang Xiong, Yuange Duan, Fang Song, Wanzhi Cai, Xuankun Li, Hu Li   +10 more
wiley   +1 more source

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

Physics‐Aware AI‐Driven 4D Temperature Reconstruction With Enhanced Non‐Uniform Vertical Resolution in Near Space (20–80 km)

Geophysical Research Letters, Volume 53, Issue 14, 28 July 2026.
Abstract Near‐space temperature is crucial for atmospheric dynamics and aerospace applications, yet data sets with refined vertical resolution remain scarce. We present the Atmospheric Spatio‐Temporal Reconstruction Network (AtmoST‐Net), which integrates high‐resolution SABER observations with dual‐source reanalysis, combining non‐uniform vertical ...
Huanwei Zhang, Yang He, Zheng Sheng
wiley   +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

FS‐Mamba: Feature‐wise scanning Mamba UNet for automatic image segmentation in liver tumor radiotherapy

Journal of Applied Clinical Medical Physics, Volume 27, Issue 7, July 2026.
Abstract Background Medical image segmentation is fundamental to radiotherapy planning, yet accurate delineation of organs at risk and tumor targets remain challenging due to anatomical variability and low soft‐tissue contrast in CT images. Purpose To develop a lightweight, high‐precision automatic segmentation network that meets the dual clinical ...
Peijun Yin, Xueren Zhang, Xin Liu, Zekun Jiang, Qingtao Qiu, Yong Yin, Zhenjiang Li   +6 more
wiley   +1 more source

A novel framework for rosacea detection using Swin Transformers and explainable artificial intelligence

Alexandria Engineering Journal
Accurate and efficient diagnosis of skin rosacea is crucial in dermatological healthcare, yet remains challenging due to the need for precise classification and interpretability.
Anjali T, S. Abhishek, Remya S
doaj   +1 more source

Efficient low‐dose CT image enhancement using MobileMamba‐UNet with wavelet‐enhanced long‐range modeling

Journal of Applied Clinical Medical Physics, Volume 27, Issue 7, July 2026.
Abstract Background Deep learning has become a dominant paradigm for low‐dose computed tomography (LDCT) image reconstruction. Nevertheless, existing approaches still struggle to simultaneously achieve accurate structural detail preservation and computational efficiency, particularly when handling long‐range contextual dependencies. Purpose To design a
Jianfang Li, Haiyan Liu, Xiaoli Wang, Jianshu Hong   +3 more
wiley   +1 more source

A self attention based deep learning framework for accurate and efficient dental disease detection in OPG radiographs

Scientific Reports
Oral diseases are increasing now-a-days and there is a high demand for the automatic diagnostic system that helps the clinician to detect these oral diseases with more accuracy and reduced human error.
Ramasubramanian Bhoopalan, S. Mirdula, Priyadharshini Kannusamy, D. Gayathri, D. Manikandan, Krishnaraj Ramaswamy   +5 more
doaj   +1 more source

Off-line identifying Script Writers by Swin Transformers and ResNeSt-50

ELCVIA Electronic Letters on Computer Vision and Image Analysis
In this work, we present two advanced models for identifying script writers, leveraging the power of deep learning. The proposed systems utilize the new vision Swin Transformer and ResNeSt-50.
Afef Kacem Echi, Takwa Ben Aïcha Gader
doaj   +1 more source