Mostrando 7 resultados de: 7
Filtros aplicados
Publisher
2022 IEEE ANDESCON: Technology and Innovation for Andean Industry, ANDESCON 2022(2)
2018 IEEE 3rd Ecuador Technical Chapters Meeting, ETCM 2018(1)
2020 IEEE ANDESCON, ANDESCON 2020(1)
IFAC-PapersOnLine(1)
Lecture Notes in Networks and Systems(1)
Área temáticas
Física aplicada(3)
Enfermedades(2)
Medicina y salud(2)
Métodos informáticos especiales(2)
Funcionamiento de bibliotecas y archivos(1)
Automatic Brain White Matter Hyperintensities Segmentation with Swin U-Net
Conference ObjectAbstract: This work proposes an automatic segmentation approach to detect White Matter Hyperintensities (WMH)Palabras claves:deep learning, segmentation, Swin-Transformer, WMHAutores:Bryan V. Piguave, Enrique Pelaez, Francis R. Loayza, José ViteriFuentes:googlescopusA Pipeline for Segmenting and Classifying Brain Lesions Caused by Stroke: A Machine Learning Approach
Conference ObjectAbstract: Brain injuries caused by strokes are one of the leading causes of disability in the world. Current pPalabras claves:Artificial Intelligence, Brain injuries, Machine learning, strokeAutores:Alex Macas, Enrique Pelaez, Francis R. Loayza, Franco-Maldonado H., Roberto MenaFuentes:scopusA deep learning model to screen for Corona Virus Disease (COVID-19) from X-ray chest images
Conference ObjectAbstract: The overwhelming situation in hospitals, both in countries considered as developed and in under-devePalabras claves:convolutional neural networks, covid-19, deep learning, X-Ray Image AnalysisAutores:Enrique Pelaez, Francis R. LoayzaFuentes:scopusFederated learning enables big data for rare cancer boundary detection
ArticleAbstract: Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizabilityPalabras claves:Autores:Agzarian M., Alexander G.S., Baid U., Bendszus M., Bhardwaj S., Bilello M., Brugnara G., Calabrese E., Capellades J., Cha S., Chang K., Chen C., Chong C., Cloughesy T.F., Currie S., Davatzikos C., Dicker A.P., Dostál M., Dou Q., Edwards B., Ellingson B.M., Enrique Pelaez, Ezhov I., Falcão A.X., Farinhas J., Fatania K., Flanders A.E., Foley P., Francis R. Loayza, Frood R., Garrett J., Ghodasara S., Gruzdev A., Hagiwara A., Haunschmidt A., Heng P.A., Holcomb J., Huang R.Y., Ingalhalikar M., Jadhav M., Jeraj R., Jiang M., Jones C.K., Karkada D., Keřkovský M., Kofler F., Kopřivová T., Kozubek M., LaMontagne P., Larson M., Liem S., Lombardo J., Lucio D.R., Lux F., Maier-Hein K., Maldjian J.A., Marcus D., Martins S.B., Matula P., Meckel S., Menotti D., Metz M., Michálek J., Mitchell J.R., Mohan S., Necker G., Oughourlian T., Palmer J.D., Pandey U., Pati S., Pichler J., Pinho M.C., Preetha C.J., Puig J., Quintero C.B., Raymond C., Reddy D., Reina G.A., Rudie J., Sahm F., Saini J., Sair H.I., Sako C., Sebastián Quevedo-Sacoto, Sheller M., Shukla G., So T.Y., Sprenger F., Teixeira B.C.A., To M.S., Trenkler J., Venkataraman A., Villanueva-Meyer J., Vogelbaum M.A., Vollmuth P., Vybíhal V., Wagner B.C., Wang C., Wang S.H., Wick W., Wiestler B., Yogananda C.G.B., Zenk M.Fuentes:scopusElectrooculography Signals Classification for FPGA-based Human-Computer Interaction
Conference ObjectAbstract: Electrooculographic techniques are applied in the development of new technologies that compensate foPalabras claves:Electrooculography, Fpga, Human-computer InteractionAutores:Diego Hernán Peluffo-Ordóñez, Enrique Pelaez, Francis R. Loayza, Jesus Miranda, Leiber Rivas, Miranda J., Otilia Alejandro, Victor Asanza ArmijosFuentes:scopusEMG Signal Processing with Clustering Algorithms for motor gesture Tasks
Conference ObjectAbstract: Recent research shows the possibility of using electromyography (EMG) electrical signals to controlPalabras claves:Butterworth Filter, DBscan, Electromyography, Fast fourier transform, hierarchical-clustering, K-MeansAutores:Diaz J., Edwin Valarezo Anazco, Enrique Pelaez, Francis R. Loayza, Mesa I., Victor Asanza ArmijosFuentes:scopusSSVEP-EEG signal classification based on emotiv EPOC BCI and raspberry pi
Conference ObjectAbstract: This work presents the experimental design for recording Electroencephalography (EEG) signals in 20Palabras claves:Brain computer interface, classification, Data acquisition, Machine learning, SSVEP-EEG, XGBoostAutores:Enrique Pelaez, Félix Rosales-Uribe, Francis R. Loayza, Hector Trivino-Gonzalez, Jamil Torres-Brunes, Karla Avilés-Mendoza, Raquel Tinoco-Egas, Ricardo Alfredo Cajo Diaz, Victor Asanza ArmijosFuentes:scopus