Results 71 to 80 of about 54,299 (266)

Claustrum Involvement in New Onset Refractory Status Epilepticus: A Systematic Review

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT The claustrum sign is a distinctive neuroimaging finding characterized by bilateral T2/FLAIR hyperintensity of the claustrum, one of the most interconnected regions of the human brain. It was first described in new‐onset refractory status epilepticus (NORSE) and febrile infection–related epilepsy syndrome (FIRES).
Margherita Burani, Lorenzo Muccioli, Giada Giovannini, Niccolò Orlandi, Francesca Bisulli, Stefano Meletti   +5 more
wiley   +1 more source

Automatic Modulation Classification Using Hybrid Data Augmentation and Lightweight Neural Network

Sensors, 2023
Automatic modulation classification (AMC) plays an important role in intelligent wireless communications. With the rapid development of deep learning in recent years, neural network-based automatic modulation classification methods have become ...
Fan Wang, Tao Shang, Chenhan Hu, Qing Liu   +3 more
doaj   +1 more source

Homological Convolutional Neural Networks

CoRR, 2023
Deep learning methods have demonstrated outstanding performances on classification and regression tasks on homogeneous data types (e.g., image, audio, and text data). However, tabular data still pose a challenge, with classic machine learning approaches being often computationally cheaper and equally effective than increasingly complex deep learning ...
Antonio Briola, Yuanrong Wang, Silvia Bartolucci, Tomaso Aste   +3 more
openaire   +3 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Irregular Convolutional Neural Networks [PDF]

2017 4th IAPR Asian Conference on Pattern Recognition (ACPR), 2017
7 pages, 5 figures, 3 ...
Jiabin Ma, Wei Wang 0115, Liang Wang 0001   +2 more
openaire   +2 more sources

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Hybrid network model based on 3D convolutional neural network and scalable graph convolutional network for hyperspectral image classification

IET Image Processing, 2023
Hyperspectral images (HSIs) contain hundreds of continuous spectral bands and are rich in spectral‐spatial information. In terms of HSIs’ classification, traditional convolutional neural networks (CNNs) extract features based on HSI's spectral‐spatial ...
Xili Wang, Zhengyin Liang
doaj   +1 more source

Clickbait Convolutional Neural Network [PDF]

Symmetry, 2018
With the development of online advertisements, clickbait spread wider and wider. Clickbait dissatisfies users because the article content does not match their expectation. Thus, clickbait detection has attracted more and more attention recently. Traditional clickbait-detection methods rely on heavy feature engineering and fail to distinguish clickbait ...
Hai-Tao Zheng 0002, Jin-Yuan Chen, Xin Yao, Arun Kumar Sangaiah, Yong Jiang 0001, Cong-Zhi Zhao   +5 more
openaire   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source