A review on extreme learning machine
Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward
neural network (SLFN), which converges much faster than traditional methods and yields …
neural network (SLFN), which converges much faster than traditional methods and yields …
A comprehensive survey on convolutional neural network in medical image analysis
CNN is inspired from Primary Visual (V1) neurons. It is a typical deep learning technique
and can help teach machine how to see and identify objects. In the most recent decade …
and can help teach machine how to see and identify objects. In the most recent decade …
Subject-independent emotion recognition of EEG signals based on dynamic empirical convolutional neural network
S Liu, X Wang, L Zhao, J Zhao, Q Xin… - … /ACM transactions on …, 2020 - ieeexplore.ieee.org
Affective computing is one of the key technologies to achieve advanced brain-machine
interfacing. It is increasingly concerning research orientation in the field of artificial …
interfacing. It is increasingly concerning research orientation in the field of artificial …
Diagnosis of secondary pulmonary tuberculosis by an eight-layer improved convolutional neural network with stochastic pooling and hyperparameter optimization
To more efficiently diagnose secondary pulmonary tuberculosis, we build an improved
convolutional neural network (ICNN) based on recent deep learning technologies. First, a 12 …
convolutional neural network (ICNN) based on recent deep learning technologies. First, a 12 …
Machine learning model for hepatitis C diagnosis customized to each patient
Machine learning is now widely used in various fields, and it has made a big splash in the
field of disease diagnosis. But traditional machine learning models are general-purpose …
field of disease diagnosis. But traditional machine learning models are general-purpose …
Glomerulus classification via an improved GoogLeNet
Glomerulosclerosis is a pathomorphological feature of glomerular lesions. Early detection,
accurate judgement and effective prevention of the glomeruli is crucial not only for people …
accurate judgement and effective prevention of the glomeruli is crucial not only for people …
Mixing patterns in social trust networks: A social identity theory perspective
Mixing patterns (MPs) in social trust networks (STNs) are increasingly attracting attention
because they can assist analysts in designing information dissemination tactics and …
because they can assist analysts in designing information dissemination tactics and …
Deep residual learning with dilated causal convolution extreme learning machine
A Sasou - IEEE Access, 2021 - ieeexplore.ieee.org
A feedforward neural network with random weights (RW-FFNN) uses a randomized feature
map layer. This randomization enables the optimization problem to be replaced by a …
map layer. This randomization enables the optimization problem to be replaced by a …
[PDF][PDF] Cross-Domain TSK Fuzzy System Based on Semi-Supervised Learning for Epilepsy Classification.
Z Cheng, Y Tao, X Gu, Y Jiang… - … -Computer Modeling in …, 2023 - cdn.techscience.cn
Through semi-supervised learning and knowledge inheritance, a novel Takagi-Sugeno-
Kang (TSK) fuzzy system framework is proposed for epilepsy data classification in this study …
Kang (TSK) fuzzy system framework is proposed for epilepsy data classification in this study …
Fetal Heart Rate Analysis from a Multi-task Learning Perspective with Gaussian Processes
Assessments of fetal heart rate tracings by obstetricians suffer from inter-and intra-observer
variability whereas computerized fetal heart rate analysis lacks consensus on labels that …
variability whereas computerized fetal heart rate analysis lacks consensus on labels that …