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Mostrando publicaciones 21-30 de 31
Automatic generation of synthetic palm vein images: a nature-based approach
(2021)
Biometric systems are essential in modern society because of the growing demand for security. Palm vein patterns have become an emerging biometric trait during the last decade. Despite that, the publicly available datasets ...
Training of an extreme learning machine autoencoder based on an iterative shrinkage-thresholding optimization algorithm
(2022)
Orthogonal transformations, proper decomposition, and the Moore–Penrose inverse are traditional methods of obtaining the output layer weights for an extreme learning machine autoencoder. However, an increase in the number ...
Water status estimation of cherry trees using infrared thermal imagery coupled with supervised machine learning modeling
(2022)
The implementation of artificial intelligence (AI) in parallel with remote sensing could be a powerful tool to manage irrigation scheduling on crops with narrow thresholds between water stress levels, such as cherry trees. ...
Parallel methods for linear systems solution in extreme learning machines: an overview
(2020)
This paper aims to present an updated review of parallel algorithms for solving square and rectangular single and double precision matrix linear systems using multi-core central processing units and graphic processing ...
Fingerprint classification through standard and weighted extreme learning machines
(2020)
Fingerprint classification is a stage of biometric identification systems that aims to group fingerprints and reduce search times and computational complexity in the databases of fingerprints. The most recent works on this ...
Detection of Parkinson’s disease based on spectrograms of voice recordings and Extreme Learning Machine random weight neural networks
(2023)
Parkinson’s disease consists in the degeneration of the mesencephalic black substance, affecting the dopaminergic vias. Its causes are varied, including exposure to pesticides, genetic factors and, one of the most influential ...
Estimation of the optimal number of neurons in extreme learning machine using simulated annealing and the golden section
(2023)
Extreme learning machine is a neural network algorithm widely accepted in the scientific community due to the simplicity of the model and its good results in classification and regression problems; digital image processing, ...
A comprehensive review of extreme learning machine on medical imaging
(2023)
The feedforward neural network based on randomization has been of great interest in the scientific community, particularly extreme learning machines, due to its simplicity, training speed, and levels of accuracy comparable ...
A parallel computing method for the computation of the Moore-Penrose generalized inverse for shared-memory architectures
(2023)
The computation of the Moore–Penrose generalized inverse is a commonly used operation in various fields such as the training of neural networks based on random weights. Therefore, a fast computation of this inverse is ...
Metagenomic binning based on unsupervised extreme learning machine
(2023)
Metagenomics studies the genetic information of microbial communities in different contexts. As metagenomic DNA is often fragmented and then sequenced into small reads, these reads can be assembled into longer sequences ...