Results 51 to 60 of about 5,267,034 (238)

Facial Expression Recognition Using Hierarchical Features With Three-Channel Convolutional Neural Network

IEEE Access, 2023
Aiming at the problem of insufficient feature extraction and low recognition rate of traditional convolutional neural network in facial expression recognition, a multi-layer feature recognition algorithm based on three-channel convolutional neural ...
Ying He, Yanxia Zhang, Shuxin Chen, Yu Hu   +3 more
doaj   +1 more source

Path integral based convolution and pooling for graph neural networks [PDF]

, 2020
Graph neural networks (GNNs) extends the functionality of traditional neural networks to graph-structured data. Similar to CNNs, an optimized design of graph convolution and pooling is key to success.
Lio P., Wang Y. G., Ma Z., Li M., Xuan J.   +4 more
core  

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

Arthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein, David J. Hunter, C. Kent Kwoh, Wolfgang Wirth   +3 more
wiley   +1 more source

Expression Recognition Algorithm of Deeply Separable Residual Network under Joint Loss

Journal of Harbin University of Science and Technology, 2023
In order to enhance the feature extraction ability of neural network and further improve the accuracy of facial expression recognition, this paper proposes a deep separable residual network model under joint loss DSResNet-Jloss.This network is a ...
LI Jingyu, CHENG Weiyue, LIN Kezheng, MIAO Zhuang, LI Ao   +4 more
doaj   +1 more source

Automated Hand Flexor Tendon–Thickness Measurement in Systemic Sclerosis

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasonography and measured manually, a time‐consuming process prone to interobserver variability.
Mark Greveling, Ties van het Erve, Yvette van de Berg, Simon Mastbergen, Julia Spierings   +4 more
wiley   +1 more source

A neural network for counter-terrorism [PDF]

, 2011
This article presents findings concerned with the use of neural networks in the identification of deceptive behaviour. A game designed by psychologists and criminologists was used for the generation of data used to test the appropriateness of different ...
M.B. Dixon, J. Elliott, Dixon, S. J., E. Guest, S.J. Dixon, D. J. Mullier, Elliott, J, Mullier, DJ, Dixon, M. B., Mullier, D. J., Elliott, J., Guest, E, Dixon, MB, Guest, E., Dixon, SJ   +14 more
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Network traffic classification method basing on CNN

Tongxin xuebao, 2018
Since the feature selection process will directly affect the accuracy of the traffic classification based on the traditional machine learning method,a traffic classification algorithm based on convolution neural network was tailored.First,the min-max ...
Yong WANG, Huiyi ZHOU, Hao FENG, Miao YE, Wenlong KE   +4 more
doaj   +2 more sources

Spike buffer: improve deep network performance by offset mechanism

The Journal of Engineering, 2020
For a well-designed neural network model, it is difficult to further improve its performance. This study proposes an offset mechanism called spike buffer, which can effectively improve the performance of the designed convolutional neural networks.
Daihui Li, Shangyou Zeng, Chengxu Ma
doaj   +1 more source

A Stacking Algorithm for Convolution Neural Network [PDF]

Jisuanji gongcheng, 2018
In order to improve the classification accuracy of convolution neural network,an improved Stacking algorithm combining multiple convolution neural networks is proposed.The convolution neural network is used as the base classifier to classify the data,and
ZHANG Xiaoming,WANG Zhijun,LIANG Liping
doaj   +1 more source