Advanced Artificial Neural Networks

Chen, Toly; Liu, Cheng-Li; Lin, Hong-Dar

doi:10.3390/a11070102

Cited by 15 publications

(8 citation statements)

References 6 publications

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“…El funcionamiento varía según la tarea y el algoritmo utilizado para lograrlo, sin embargo, en esencia, un modelo de aprendizaje automático es una computadora que analiza datos e identifica patrones, y luego usa esos conocimientos para completar mejor la tarea asignada [15]. Cuando las tareas dependen de un conjunto de datos o reglas se pueden automatizar mediante el aprendizaje automático y dependiendo de la situación, los algoritmos de aprendizaje automático funcionan con más o menos intervención/refuerzo humano [16]; cuando la computadora recibe un conjunto de datos etiquetados que le permite aprender cómo realizar una tarea humana se dice que el algoritmo aplica aprendizaje supervisado. Aquí la intervención del ser humano es de mucha importancia a la hora de etiquetar adecuadamente e conjunto de datos y los algoritmos intentan replicar el aprendizaje humano [17].…”

Section: B Tratamientosunclassified

Application of Machine Learning for the Prediction of Covid19 Through Classification Techniques and Supervised Learning

Molina¹,

Crespo²,

Reyes³

et al. 2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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In January 2020, in the city of Wuhan in China, a highly dangerous disease for humans appeared, cataloged as COVID-19 and caused by a virus called SARS-CoV-2; This disease spread from Asia to Europe and then spread throughout the American continent, causing a pandemic that to this day continues to cause irreparable damage. Currently the virus has mutated, and its variants continue to congest health systems in all parts of the world. The spread of the virus has generated information that is available on public research-oriented portals, and that is available for scientists and researchers to have the necessary information so that they can develop strategies to face and stop the disease. Using machine learning techniques, a prediction model has been created, which by applying supervised learning performs an analysis of historical data and has learned to identify patterns, managing to identify the disease.

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Section: B Tratamientosunclassified

Application of Machine Learning for the Prediction of Covid19 Through Classification Techniques and Supervised Learning

Molina¹,

Crespo²,

Reyes³

et al. 2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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“…Las redes neuronales artificiales [4] son un tipo especial de algoritmos de aprendizaje automático [15] que se modelan a partir del cerebro humano. Es decir, al igual que las neuronas de nuestro sistema nervioso pueden aprender de los datos pasados [33], la RNA puede aprender de los datos y proporcionar respuestas en forma de predicciones o clasificaciones [34]. Las RNA son modelos estadísticos no lineales que muestran una relación compleja entre las entradas y salidas para descubrir un nuevo patrón.…”

Section: Optimizaciónunclassified

Design of a Toroidal Pressure Vessel of Carbon Fiber for Hydrogen Cars Using the Finite Element Method and Deep Learning

Pazmiño¹,

Ramírez²,

Plaza³

et al. 2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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Resumen. -El uso de hidrogeno en la industria automotriz, ha generado el diseño de nuevos recipientes a presión para su almacenamiento; los recipientes convencionales son los cilindros de metal que tienen una baja capacidad de almacenamiento y ocasionan un desperdicio de espacio en el maletero de los autos. Los recipientes toroidales de fibra de carbono son una alternativa que brindaría una mejor prestación. Se tomará el diseño de un recipiente que almacena GNC y se lo someterá a un rediseño por medio de elementos finitos (FEM) para el análisis numérico y elástico lineal de la fibra de carbono a emplearse, además se usaran Threads para acelerar el proceso de optimización y se elaborará un modelo de Red Neuronal Artificial para que aprenda a estimar el volumen de material necesario.

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“…DL is a specialized ML method and refers to algorithms inspired by the structure and function of a brain, called artificial neural networks (ANNs). 23,24 DL is currently gaining considerable attention for its usefulness with big data in healthcare. The concept of ANNs was first introduced in the 1950s; however, there were critical limitations that needed to be overcome over the following 50 years to cope with real-world problems.…”

Section: Machine Learning and Deep Learning Rise Of Aimentioning

confidence: 99%

Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy

Choi

Shin

Jung³

et al. 2020

Clin Endosc

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Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural networks suffered from overfitting and vanishing gradient problems for training deep networks. This concept has become more promising owing to the enhanced big data processing capability, improvement in computing power with parallel processing units, and new algorithms for deep neural networks, which are becoming increasingly successful and attracting interest in many domains, including computer vision, speech recognition, and natural language processing. Recent studies in this technology augur well for medical and healthcare applications, especially in endoscopic imaging. This paper provides perspectives on the history, development, applications, and challenges of deep-learning technology. clin endosc 2020;53:117-126

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Advanced Artificial Neural Networks

Cited by 15 publications

References 6 publications

Application of Machine Learning for the Prediction of Covid19 Through Classification Techniques and Supervised Learning

Application of Machine Learning for the Prediction of Covid19 Through Classification Techniques and Supervised Learning

Design of a Toroidal Pressure Vessel of Carbon Fiber for Hydrogen Cars Using the Finite Element Method and Deep Learning

Convolutional Neural Network Technology in Endoscopic Imaging: Artificial Intelligence for Endoscopy

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