• A new fast training algorithm for autoencoder neural networks based on extreme learning machine 

    Vásquez-Coronel, José A; Mora, Marco ORCID; Vilches-Ponce, Karina; Silva Pavez, Fabián; Torres-Gonzalez, Italo; Barria-Valdevenito, Pedro (2022)
    Autoencoders are neural networks that are characterized by having the same inputs and outputs. This kind of Neural Networks aim to estimate a nonlinear transformation whose parameters allow to represent the input patterns ...

  • A-Survey: identification and classification of fingerprints via the extreme learning machine algorithm 

    Zabala-Blanco, David; Martínez-Pereira, Diego; Flores-Calero, Marco; Datta, Jayanta; Dehghan Firoozabadi, Ali (2023)
    The fingerprint comes to be the most popular and utilized biometric for identifying persons owing to its bio-invariant characteristic, precision, as well as easy acquisition. A sub-system of an identification system is the ...

  • Classification of diseased and healthy apple leaves through extreme learning machines 

    Ahumada García, Roberto; Zabala-Blanco, David; Soto, Ismael; López-Cortés, Xaviera A.; Barrientos, Ricardo ORCID (2022)
    Diseases in agricultural crops are a risk for fruit productivity and quality. Chile is a fruit exporting country; that needs the development of technologies for diseases prevention and treatment. Farmers have been exploring ...

  • Evaluation of extreme learning machines for detecting heart diseases 

    Martínez, Diego; Zabala-Blanco, David; Ahumada-Garcia, Roberto; Soto, Ismael; Dehghan Firoozabadi, Ali; Palacios Játiva, Pablo (2023)
    Currently, cardiovascular diseases are the leading cause of human death according to the World Health Organization. Their prediction allows doctors to indicate preventive measures to their patients and perform procedures ...

  • Extreme learning machine (ELM) for detection of hazardous near Earth objects 

    Ahumada-García, Roberto; Morán Faúndez, Esteban; Zabala-Blanco, David; López-Cortés, Xaviera A.; Rivelli Malco, Juan Pablo; Soto, Ismael (2023)
    The protection of planet Earth, its inhabitants, and all living beings requires the identification of potentially dangerous objects, the simulation of impacts with Earth, and the mitigation of such threats. This research ...

  • Extreme learning machine for mass spectrometry data analysis 

    Ulloa Orellana, Mario; López-Cortès, Xaviera A.; Zabala-Blanco, David; Palacios Játiva, Pablo; Datta, Jayanta (2022)
    In this work, we introduce the use of a weighted extreme learning machine (ELM) to give an automated predictive value to mass spectrometry data. In specific, the data obtained with Matrix-Assisted Laser DesorptioMonization-Time ...

  • Extreme learning machines for detecting the water quality for human consumption 

    Barría Valdebenito, Pedro; Zabala-Blanco, David; Ahumada-García, Roberto; Soto, Ismael; Dehghan Firoozabadi, Ali; Flores-Calero, Marco (2023)
    Determining the potability of water for consumption is crucial for human health. To assess the water quality, levels of minerals and ions are measured, such as pH, hardness, sodium, chloramines, sulfate, conductivity, ...

  • Extreme learning machines to combat phase noise in RoF-OFDM schemes 

    Zabala-Blanco, David; Mora, Marco ORCID; Azurdia-Meza, Cesar A.; Dehghan Firoozabadi, Ali (2019)
    Radio-over-fiber (RoF) orthogonal frequency division multiplexing (OFDM) systems have been revealed as the solution to support secure, cost-effective, and high-capacity wireless access for the future telecommunication ...

  • Fast tuning of extreme learning machine neural networks based with simple optimization algorithms 

    Tobar Valenzuela, Luis; Mora, Marco ORCID; Silva Pavez, Fabián; Torres-Gonzalez, Italo; Barría-Valdebenito, Pedro (2022)
    Extreme Learning Machine (ELM) is a neural network training paradigm that is characterized by simplicity, speed and high level of accuracy. The tuning of the network parameters is normally carried out with non-linear ...

  • Fingerprint classification with the extreme learning machine algorithm for multilayer perceptron 

    Zabala-Blanco, David; Quinteros, Axel; Mora, Marco ORCID; Hernández-García, Ruber; Flores-Calero, Marco (2022)
    Fingerprint classification comes to be a relevant guarantee for efficient as well as accurate fingerprint identification, in particular in the case of dealing with one-to-many fingerprint identification. Nevertheless, owing ...

  • Multilayer extreme learning machine as equalizer in OFDM-based radio-over-fiber systems 

    Zabala-Blanco, David; Mora, Marco ORCID; Azurdia-Meza, Cesar A.; Dehghan Firoozabadi, Ali; Palacios Játiva, Pablo; Montejo-Sánchez, Samuel (2021)
    Mobile/wireless networks aim to support diverse services with numerous and sophisticated requirements, such as energy efficiency, spectral efficiency, negligible latency, robustness against time and frequency selective ...

  • Parallel training of a set of online sequential extreme learning machines 

    Gelvez-Almeida, Elkin; Barrientos, Ricardo ORCID; Vilches-Ponce, Karina; Mora, Marco ORCID (2022)
    Size databases have constantly increased from advances in technology and the Internet, so processing this vast amount of information has been a great challenge. The neural network Extreme Learning Machine (ELM) have been ...

  • PVEIN-MLELM: a novel palm vein identification approach through multilayer extreme learning machine 

    Zabala-Blanco, David; Hernández-García, Ruber; Barrientos, Jaime; Ahumada García, Roberto (2022)
    Biometric identification systems play an essential role in multiple application areas, such as banking services, e-government, and public security, among others. Particularly, palm vein recognition is considered an emerging ...

  • Review of extreme learning machines for the identification and classification of fingerprint databases 

    Martínez, Diego; Zabala-Blanco, David; Ahumada García, Roberto; Azurdia-Meza, Cesar A.; Flores-Calero, Marco; Palacios-Jativa, Pablo (2022)
    The fingerprint is one of the most popular and used biometric traits for the identification of people, due to its bio-invariant characteristic, precision, and easy acquisition. One of the stages in the identification of ...

  • Semi-supervised extreme learning machine channel estimator and equalizer for vehicle to vehicle communications 

    Salazar, E.; Azurdia-Meza, Cesar A.; Zabala-Blanco, David; Bolufé, Sandy; Soto, Ismael (2021)
    Wireless vehicular communications are a promising technology. Most applications related to vehicular communications aim to improve road safety and have special requirements concerning latency and reliability. The traditional ...

  • SoftVein-WELM: a weighted extreme learning machine model for soft biometrics on palm vein images 

    Zabala-Blanco, David; Hernández-García, Ruber; Barrientos, Ricardo ORCID (2023)
    Contactless biometric technologies such as palm vein recognition have gained more relevance in the present and immediate future due to the COVID-19 pandemic. Since certain soft biometrics like gender and age can generate ...

  • Wine quality classification using physicochemical properties along with extreme learning machines 

    Torres González, Ítalo; Zabala-Blanco, David; Ahumada-García, Roberto; Rivelli Malcó, Juan Pablo; Azurdia-Meza, Cesar A.; Palacios Játiva, Pablo (2023)
    Chilean wine is one of the most consumed in the global market due to its excellent quality and wide variety of grape crops throughout the country, with Chile being the largest exporter of wine in the southern hemisphere. ...