Mostrando 10 resultados de: 13
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)(2)
2017 IEEE 2nd Ecuador Technical Chapters Meeting, ETCM 2017(1)
2020 IEEE ANDESCON, ANDESCON 2020(1)
25th European Signal Processing Conference, EUSIPCO 2017(1)
Advances in Intelligent Systems and Computing(1)
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Métodos informáticos especiales(8)
Ciencias de la computación(7)
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Cirugía y especialidades médicas afines(1)
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2D semantic segmentation of the prostate gland in magnetic resonance images using convolutional neural networks
Conference ObjectAbstract: Convolutional Neural Networks is one of the most commonly used methods for automatic prostate segmenPalabras claves:Central Gland, convolutional neural networks, Encoder-Classifier, Encoder-Decoder, MRIs, NCI-ISBI 2013, Peripheral Zone, Prostate Segmentation, U-net, VGG16Autores:Marco E. Benalcázar, Silvia P. VacacelaFuentes:googlescopusA Brain-Computer Interface for Controlling IoT Devices using EEG Signals
Conference ObjectAbstract: Motor disability is the loss of the ability to move a limb of the body. Motor disabilities make diffPalabras claves:Bci, EEG, IOT, k-NNAutores:Kelvin Ortíz Chicaiza, Marco E. BenalcázarFuentes:scopusA Model for Real-Time Hand Gesture Recognition Using Electromyography (EMG), Covariances and Feed-Forward Artificial Neural Networks
Conference ObjectAbstract: Hand gesture recognition has many applications that require models to work in real time and with higPalabras claves:classification, EMG signals, Feed-forward neural networks, Hand gesture recognition, Myo ArmbandAutores:Anchundia V. C.E., Andrés Jaramillo-Yánez, José González, Marco E. Benalcázar, Marco Segura, Patricio ZambranoFuentes:scopusAutomatic segmentation of exudates in ocular images using ensembles of aperture filters and logistic regression
Conference ObjectAbstract: Hard and soft exudates are the main signs of diabetic macular edema (DME). The segmentation of bothPalabras claves:Autores:Ballarin V.L., Brun M., Marco E. BenalcázarFuentes:googlescopusGesture recognition and machine learning applied to sign language translation
Conference ObjectAbstract: In this paper we propose an intelligent system for translating sign language into text. This approacPalabras claves:Gesture recognition, Machine learning, Pattern classification, Sign language translationAutores:Luis Alberto Estrada Jiménez, Marco E. Benalcázar, Nelson SotomayorFuentes:googlescopusHand gesture recognition using machine learning and the myo armband
Conference ObjectAbstract: Gesture recognition has multiple applications in medical and engineering fields. The problem of handPalabras claves:Autores:Andrés G. Jaramillo, Andrés Jaramillo-Yánez, Jonathan A. Zea, Marco E. Benalcázar, Víctor Hugo AndaluzFuentes:scopusReal-Time Hand Gesture Recognition: A Long Short-Term Memory Approach with Electromyography
Conference ObjectAbstract: Hand gestures are a non-verbal type of communication ideally suited for Human-Machine Interaction. NPalabras claves:EMG, Hand gesture recognition, LSTM, Myo ArmbandAutores:Jonathan A. Zea, Marco E. BenalcázarFuentes:googlescopusReal-time hand gesture recognition based on artificial feed-forward neural networks and EMG
Conference ObjectAbstract: In this paper, we propose a real-time hand gesture recognition model. This model is based on both aPalabras claves:Electromyography, Feature Extraction, Feed-forward neural networks, Hand gesture recognition, real-time, TIME SERIESAutores:Anchundia V. C.E., Andrés G. Jaramillo, Jonathan A. Zea, Marco E. Benalcázar, Marco Segura, Patricio Xavier Zambrano Rodríguez, Patricio ZambranoFuentes:googlescopusReal-time hand gesture recognition based on electromyographic signals and artificial neural networks
Conference ObjectAbstract: In this paper, we propose a hand gesture recognition model based on superficial electromyographic siPalabras claves:artificial neural networks, Electromyography, Hand gesture recognition, Machine learning, Signal processingAutores:Cristhian Motoche, Marco E. BenalcázarFuentes:scopusReal-time hand gesture recognition with EMG using machine learning
Conference ObjectAbstract: In this paper, we propose the development of a model for real-time hand gesture recognition. We usePalabras claves:EMG(Electromyography), Hand gesture recognition, Machine learning, real-timeAutores:Andrés G. Jaramillo, Marco E. BenalcázarFuentes:scopus