Results 51 to 60 of about 740 (176)

Improved Integral Anti‐Saturation‐Based Grid‐Connected Performance Method and Optimized DC Voltage Control for Grid‐Forming SVG

IET Power Electronics, Volume 19, Issue 1, January/December 2026.
To overcome these challenges, this study establishes a direct linear correlation between the DC form of zero‐sequence voltage and the phase‐cluster voltage deviation. Based on this correlation, an optimized GFSVG phase‐voltage balancing control strategy using zero‐sequence voltage superposition is proposed.
Haijun Liu, Kai Hu, Guoliang Zhao, Zhong Fu, Mengze Wu, Aihua Zhao, Dan Hu   +6 more
wiley   +1 more source

Comparative study for image registration techniques of remote sensing images

Egyptian Journal of Remote Sensing and Space Sciences, 2010
Image registration determines the relative orientation between two images. As there are different techniques for image registration, it is important to compare these techniques to identify the advantages and disadvantages of each one.
R.M. Ezzeldeen, H.H. Ramadan, T.M. Nazmy, M. Adel Yehia, M.S. Abdel-Wahab   +4 more
doaj   +1 more source

Spatial‐Temporal Feature Fusion Network for Short‐Term Photovoltaic Forecasting Utilising Multi‐Source Heterogeneous Data

IET Renewable Power Generation, Volume 20, Issue 1, January/December 2026.
Integrates multi‐grid meteorological data for improved prediction accuracy. SCBAM dynamically adjusts spatial feature weights to focus on key meteorological correlations. Adopts UNet‐based multi‐scale feature fusion to preserve fine‐grained spatial‐temporal patterns.
Ping Yang, Zhuolin Zhong, Yingxuan Sun, Yuxuan Lin   +3 more
wiley   +1 more source

A Bayesian‐Optimized Ensemble Deep Learning Framework for Automated Detection and Classification of Retinal Diseases in Ghana Using OCT Images

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Retinal diseases pose a significant global health challenge due to their potential to cause severe visual impairment and blindness. This study aimed to develop a robust deep learning ensemble framework for the automated detection and classification of retinal diseases from optical coherence tomography (OCT) images.
Gifty Duah, Eric Nyarko, Gideon Nana Amo, Theophilus Dwamena Frimpong, Anani Lotsi, Pramita Mishra   +5 more
wiley   +1 more source

Attention‐Enhanced Hybrid CNN–Transformer Approach Using ResNeXt‐50 and Swin Transformer for Apple Leaf Disease Classification

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Apple leaf diseases critically affect fruit yield and quality. Rapid and accurate field diagnosis remains challenging due to variable lighting, complex backgrounds, and environmental noise. We propose a robust hybrid deep learning framework that effectively combines convolutional neural networks for fine‐grained local feature extraction with vision ...
Vishal Thakur, Ravindara Bhatt, R. S. Raja Durai, Satish Kumar, Mukesh Kumar   +4 more
wiley   +1 more source

A Hierarchical Multimodal AI Framework for Intelligent Alarm Handling in Smart Power Grid Monitoring Systems

International Transactions on Electrical Energy Systems, Volume 2026, Issue 1, 2026.
Recent developments and the rapid expansion of modern power grids have led to alarm flooding. This means that operators receive such a large volume of alarms that they become overwhelmed and stall in inquiry, resulting in mistakes. To better address this issue, an innovative, multifaceted, and hierarchical framework is proposed that combines stability ...
Tairan Li, Qingpeng Wang, Gao Yang, Qiang Huang, Qingqing Ren, Hao Yang, Huamin Jie   +6 more
wiley   +1 more source

The Role of Machine Learning in Addressing Antibiotic Resistance: A New Era in Infectious Disease Control

MicrobiologyOpen, Volume 14, Issue 6, December 2025.
Artificial intelligence accelerates the discovery of new antibiotics by rapidly analyzing vast chemical libraries to combat antimicrobial resistance effectively. AI systems predict antibiotic resistance trends, helping researchers design targeted therapies, and prevent the spread of multidrug‐resistant infections. ABSTRACT Antimicrobial resistance (AMR)
Akmal Zubair, Mohd Fazil, Muhammad Jawad, Safa Wdidi   +3 more
wiley   +1 more source

Applications of Artificial Intelligence in Neurological Voice Disorders

World Journal of Otorhinolaryngology - Head and Neck Surgery, Volume 11, Issue 4, Page 491-517, December 2025.
ABSTRACT Neurological voice disorders, such as Parkinson's disease, laryngeal dystonia, and stroke‐induced dysarthria, significantly impact speech production and communication. Traditional diagnostic methods rely on subjective assessment, whereas artificial intelligence (AI) offers objective, noninvasive, and scalable solutions for voice analysis. This
Dongren Yao, Aki Koivu, Kristina Simonyan   +2 more
wiley   +1 more source

Robust Mammogram Denoising Under Extreme Impulse Noise via FLBMF‐Selective Median‐TV Hybrid Scheme

Engineering Reports, Volume 7, Issue 10, October 2025.
(a–g) Original, degraded, and denoised DDSM Mammogram A_0042_1.RIGHT_CC.jpg, S, and P noise densities: 10%, 20%, 40%, 60%, 70%, 80%, and 90%. ABSTRACT Critical for the early detection and precise diagnosis of breast cancer, mammogram imaging risks encountering extreme impulse noise which, in some cases, occurs at levels between 60% and 90%.
Benard Nyangena Kiage, Wilson K. Cheruiyot, Michael W. Kimwele   +2 more
wiley   +1 more source

NSCT‐PCNN image fusion based on image gradient motivation

IET Computer Vision, 2018
Pulse coupled neural network (PCNN) is widely used in image processing because of its unique biological characteristics, which is suitable for image fusion.
Shifei Ding, Xingyu Zhao, Hui Xu, Qiangbo Zhu, Yu Xue   +4 more
doaj   +1 more source