J. Cuevas-Tello

发表

Kernel regression estimates of time delays between gravitationally lensed fluxes

Sultanah Al Otaibi, I. Mandel, Somak Raychaudhury, 2015, 1508.03439.

Multi-Objective Optimisation in Time Series : Time Delay Agreement

J. Cuevas-Tello, H. G. Pérez-González, 2011 .

1 Novel Risk Assessment Methodology for Keyhole 2 Neurosurgery with Genetic Algorithm for Trajectory 3 Planning 4

Cesar A. Puente-Montejano, J. Cuevas-Tello, R. Aguilar-Ponce, 2018 .

Risk assessment methodology for trajectory planning in keyhole neurosurgery using genetic algorithms

Carlos Soubervielle-Montalvo, Saúl Tovar-Arriaga, Iván Villanueva-Naquid, 2019, The international journal of medical robotics + computer assisted surgery : MRCAS.

Identification of HIV-1 Vif Protein Attributes Associated With CD4 T Cell Numbers and Viral Loads Using Artificial Intelligence Algorithms

Jose S. Altamirano-Flores, Sandra E. Guerra-Palomares, Pedro G. Hernandez-Sanchez, 2020, IEEE Access.

KIR Genes and Patterns Given by the A Priori Algorithm: Immunity for Haematological Malignancies

Juan Carlos Cuevas-Tello, Christian Alberto Garcia-Sepulveda, J. Gilberto Rodríguez-Escobedo, 2015, Comput. Math. Methods Medicine.

Support vector machine algorithms in the search of KIR gene associations with disease

Juan Carlos Cuevas-Tello, Christian Alberto Garcia-Sepulveda, Daniel Hernández-Ramírez, 2013, Comput. Biol. Medicine.

IT Services for Decision Support Systems on Public Health Problems by using Genomic Data

Manuel Mora Tavarez, Hector G. Pérez-González, Juan Carlos Cuevas-Tello, 2010, BIOCOMP.

Ontology for knowledge condensation to support expertise location in the code phase during software development process

Ramon R. Palacio, Gilberto Borrego, Jose R. Martínez-Garcia, 2020, IET Softw..

Computational Forecasting Methodology for Acute Respiratory Infectious Disease Dynamics

Juan Carlos Cuevas-Tello, Daniel Alejandro Gónzalez-Bandala, Daniel E Noyola, 2020, International journal of environmental research and public health.

Estimating time delays between irregularly sampled time series

Juan Carlos Cuevas-Tello, J. Cuevas-Tello, 2007 .

Fruit Classification for Retail Stores Using Deep Learning

J. C. Cuevas-Tello, Jose Luis Rojas-Aranda, Jose Ignacio Nunez-Varela, 2020, MCPR.

A Methodology for Obtaining Universal Software Code Metrics

Juan C. Cuevas-Tello, Carlos Soubervielle-Montalvo, Alberto S. Núñez-Varela, 2013 .

Design of a Low-Power Embedded System Based on a SoC-FPGA and the Honeybee Search Algorithm for Real-Time Video Tracking

Oscar E. Perez-Cham, Cesar Puente, C. Aguirre-Salado, 2022, Sensors.

Parallel Approach for Time Series Analysis with General Regression Neural Networks

Juan C. Cuevas-Tello, Omar Vital-Ochoa, Hector G. Perez-Gonzalez, 2012 .

Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application

Peter Tiño, Markus Harva, Xin Yao, 2009, Pattern Recognit..

Identification of Clinically Relevant HIV Vif Protein Motif Mutations through Machine Learning and Undersampling

P. Tiňo, C. García-Sepúlveda, J. Cuevas-Tello, 2023, Cells.

Building a User Oriented Application for Generic Source Code Metrics Extraction from a Metrics Framework

Alberto S. Núñez-Varela, Alberto S. Nunez-Varela, Francisco E. Martinez-Perez, 2016, 2016 4th International Conference in Software Engineering Research and Innovation (CONISOFT).

Estimating Time Delay in Gravitationally Lensed Fluxes Extended Abstract

P. Tiňo, Somak Raychaudhury, J. Cuevas-Tello, 2009 .

A Deep Learning Model Based on Capsule Networks for COVID Diagnostics through X-ray Images

J. Cuevas-Tello, Gabriela Rangel, Mariano Rivera, 2023, Diagnostics.

Uncovering delayed patterns in noisy and irregularly sampled time series: An astronomy application

M. Harva, Somak Raychaudhury, J. Cuevas-Tello, 2009, Pattern Recognit..

A Kernel-Based Approach to Estimating Phase Shifts Between Irregularly Sampled Time Series: An Application to Gravitational Lenses

Peter Tiño, Juan C. Cuevas-Tello, Somak Raychaudhury, 2006, ECML.

Analysis of Time Series with Artificial Neural Networks

R.A. Gonzalez-Grimaldo, J.C. Cuevas-Tello, J. Cuevas-Tello, 2008, 2008 Seventh Mexican International Conference on Artificial Intelligence.

A Tutorial on Deep Neural Networks for Intelligent Systems pdf

Juan Arturo Nolazco-Flores, Juan C. Cuevas-Tello, Manuel Valenzuela-Rendón, 2016, ArXiv.

A Survey on Convolutional Neural Networks and Their Performance Limitations in Image Recognition Tasks

J. Cuevas-Tello, Gabriela Rangel, J. Nuñez-Varela, 2024, Journal of Sensors.

Activity Inference for Ambient Intelligence Through Handling Artifacts in a Healthcare Environment

Marcela D. Rodríguez, Juan C. Cuevas-Tello, Francisco E. Martínez-Pérez, 2012, Sensors.