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260 results on '"Gamboa-Rosales, Hamurabi"'

1. Convolutional Neural Network for Monkeypox Detection

Author

Alcalá-Rmz, Vanessa, Villagrana-Bañuelos, Karen E., Celaya-Padilla, José M., Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Galván-Tejada, Carlos E., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Bravo, José, editor, Ochoa, Sergio, editor, and Favela, Jesús, editor

Published
2023
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2. Towards Esophagitis and Barret’s Esophagus Endoscopic Images Classification: An Approach with Deep Learning Techniques

Author

Villagrana-Bañuelos, Karen E., Alcalá-Rmz, Vanessa, Celaya-Padilla, José M., Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Galván-Tejada, Carlos E., Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Bravo, José, editor, Ochoa, Sergio, editor, and Favela, Jesús, editor

Published
2023
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3. Past, current and future of fuel cell technologies: A bibliometric analysis of the research published during the 1968-2018 period

Author

Gamboa-Rosales, Nadia-Karina, Ayastuy-Arizti, Jose-Luis, Gamboa-Rosales, Hamurabi, Galván-Tejada, Carlos-Eric, Luna-García, Huizilopoztli, Galván-Tejada, Jorge-Issac, Celaya-Padilla, José-María, Otegi-Olaso, Jose-Ramón, and López-Robles, José-Ricardo

Subjects
BA. Use and impact of information., BB. Bibliometric methods, FJ. Knowledge management
Abstract

CONTEXT Fuel-Cell technologies have evolved from being an emerging topic to a growing research area in business, science and education fields. The Fuel-Cell technologies have a multidimensional approach. This research presents a comprehensive review of different fuel cell technologies with their working principle, evolution, relationship and suitability of applications for transportation. The professionals and researches involved in this area of knowledge are seeking to uncover the conceptual structure and define a roadmap to reduce the time of research, development, testing/validation and industrialization. OBJECTIVE The main aim of this contribution is to develop a bibliometric analysis to evaluate the performance and conceptual evolution of the Fuel-Cell technologies from 1968 to 2018. The analysis is developed using SciMAT.

Published
2019

4. Visualizing and Mapping the Project Management Research Areas withing the International Journal of Project Management: A bibliometric analysis from 1983 to 2018

Author

López-Robles, José-Ricardo, Otegi-Olaso, Jose-Ramón, Gamboa-Rosales, Nadia-Karina, Gamboa-Rosales, Hamurabi, Robles-Berumen, Hermes, and Gamboa-Rosales, Abubeker

Subjects
B. Information use and sociology of information, BB. Bibliometric methods, BG. Information dissemination and diffusion.
Abstract

CONTEXT. Project Management has evolved from being an emerging topic to a growing research area in business, science and education fields. The Project Management concept has a multidimensional approach, and it can be defined as the practice of initiating, planning, executing, controlling, and closing the work of a team to achieve specific goals and meet specific success criteria at the specified time. The professionals involved in this area of knowledge are seeking to uncover the conceptual structure of a research area of interest are worth and necessary. OBJECTIVE. The main aim of this contribution is to develop a bibliometric analysis to evaluate the performance and conceptual evolution of the Project Management research themes from 1983 to 2018. SOFTWARE. The analysis is developed using SciMAT.

Published
2019

5. Bibliometric network to identify the intellectual structure and evolution of the big data research field

Author

López-Robles, José-Ricardo, Otegi-Olaso, José-Ramón, Porto-Gómez, Igone, Gamboa-Rosales, Nadia-Karina, Gamboa-Rosales, Hamurabi, and Robles-Berumen, Hermes

Subjects
BA. Use and impact of information., BB. Bibliometric methods, FJ. Knowledge management
Abstract

Big Data has evolved from being an emerging topic to a growing research area in business, science and education fields. The Big Data concept has a multidimen-sional approach, and it can be defined as a term describing the storage and analy-sis of large and complex data sets using a series of advanced techniques. In this respect, the researches and professionals involved in this area of knowledge are seeking to develop a culture based on data science, analytics and intelligence. To this end, it is clear that there is a need to identify and examine the intellectual structure, current research lines and main trends. In this way, this paper reviews the literature on Big Data evaluating 23,378 articles from 2012 to 2017 and offers a holistic approach of the research area by using SciMAT as a bibliometric and network analysis software. Furthermore, it evaluates the top contributing authors, countries and research themes that are directly related to Big Data. Finally, a sci-ence map is developed to understand the evolution of the intellectual structure and the main research themes related to Big Data.

Published
2018

6. Inteligencia: origen, evolución y tendencias (Intelligence: origin, evolution and trends)

Author

López-Robles, José-Ricardo, Otegi-Olaso, José-Ramón, Porto-Gómez, Igone, Gamboa-Rosales, Hamurabi, and Gamboa-Rosales, Nadia-Karina

Subjects
BA. Use and impact of information., BB. Bibliometric methods, BD. Information society., BH. Information needs and information requirements analysis.
Abstract

In the knowledge economy era, information has become the main asset of organizations, regardless of their typology. In response to this scenario, organizations have opted for the active application of intelligence models based on knowledge of the cultural, social, political, business and technological environment from a holistic, dynamic and flexible point of view. This has favored the emergence of new approaches to Intelligence, which like the more traditional approaches, seek to collect, analyze, interpret and disseminate high value data and information at the right time for use in decision-making processes. However, this does not mean that organizations should assume that more traditional intelligence strategies continue to be viable, on the contrary, the "new rules of the game" are currently being defined and therefore we face completely radical changes. In this sense, it is necessary to review the origins of the concept of intelligence to capture the essence, analyze its evolution and consider trends, with the aim of rethinking and redesigning the concept of Intelligence from an integrative approach, regardless of the nuance or scope of application that our organizations are using. The idea of having a single framework of Intelligence adapted to the reality of the organizations will bring with it a greater diffusion of this discipline and a series of advantages for the organizations themselves. In order to achieve this, a detailed analysis of all existing publications in the literature is proposed through tools specialized in the treatment of large amounts of information. From this analysis, we will obtain the current picture of the concept of intelligence, its main lines of work and research, as well as short/medium term trends.

Published
2018

7. Intelligence: origin, evolution and trends (Inteligencia: origen, evolución y tendencias)

Author

López-Robles, José-Ricardo, Otegi-Olaso, José-Ramón, Porto-Gómez, Igone, Gamboa-Rosales, Hamurabi, and Gamboa-Rosales, Nadia-Karina

Subjects
BA. Use and impact of information., BB. Bibliometric methods, BC. Information in society., BG. Information dissemination and diffusion., ID. Knowledge representation., IF. Information transfer: protocols, formats, techniques., IM. Open data, LP. Intelligent agents.
Abstract

In the knowledge economy era, information has become the main asset of organizations, regardless of their typology. In response to this scenario, organizations have opted for the active application of intelligence models based on knowledge of the cultural, social, political, business and technological environment from a holistic, dynamic and flexible point of view. This has favored the emergence of new approaches to Intelligence, which like the more traditional approaches, seek to collect, analyze, interpret and disseminate high value data and information at the right time for use in decision-making processes. However, this does not mean that organizations should assume that more traditional intelligence strategies continue to be viable, on the contrary, the "new rules of the game" are currently being defined and therefore we face completely radical changes. In this sense, it is necessary to review the origins of the concept of intelligence to capture the essence, analyze its evolution and consider trends, with the aim of rethinking and redesigning the concept of Intelligence from an integrative approach, regardless of the nuance or scope of application that our organizations are using. The idea of having a single framework of Intelligence adapted to the reality of the organizations will bring with it a greater diffusion of this discipline and a series of advantages for the organizations themselves. In order to achieve this, a detailed analysis of all existing publications in the literature is proposed through tools specialized in the treatment of large amounts of information. From this analysis, we will obtain the current picture of the concept of intelligence, its main lines of work and research, as well as short/medium term trends.

Published
2018

8. Driver Identification Using Machine Learning and Motor Activity as Data Source

Author

Espino-Salinas, Carlos H., Luna-García, Huizilopoztli, Celaya-Padilla, José M., Morgan-Benita, Jorge A., Sarmiento, Wilson J., Gamboa-Rosales, Hamurabi, Galván-Tejada, Jorge I., Galván-Tejada, Carlos E., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Agredo-Delgado, Vanessa, editor, Ruiz, Pablo H., editor, and Correa-Madrigal, Omar, editor

Published
2022
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12. 60 years of Business Intelligence: a Bibliometric Review from 1958 to 2017

Author

López-Robles, José-Ricardo, Otegi-Olaso, José-Ramón, Gamboa-Rosales, Nadia-Karina, Gamboa-Rosales, Hamurabi, and Cobo-Martín, Manuel-Jesús

Subjects
B. Information use and sociology of information, BA. Use and impact of information., BB. Bibliometric methods, FJ. Knowledge management, FZ. None of these, but in this section.
Abstract

Business Intelligence (BI) is being seen as a core activity in business, science, education or any field in which the use of intelligent software are vital to achieve their goals. The BI concept is also multidimensional, and it can be defined as a technology-driven process for analyzing data and presenting actionable information to support the organizational decisions. In this respect, the professionals involved in this area of knowledge are seeking to develop a culture of result orientation, focused on an effective decision-making and collaboration. Thus, the main aim of this contribution is to develop a bibliometric analysis to evaluate the performance and conceptual evolution of the authors and publications that are directly related to Business Intelligence.

Published
2018

13. Desktop Application for Water Quality Prediction and Monitoring System Using ISO 9241-210 and Machine Learning Techniques

Author

Guzman-Fernandez, Maximiliano, Luna-García, Huizilopoztli, Collazos, Cesar A., Sarmiento, Wilson J., Galvan-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Galvan-Tejada, Carlos E., Celaya-Padilla, Jose M., Zambrano-de la Torre, Misael, Lara-Cisneros, J. Guadalupe, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Ruiz, Pablo H., editor, Agredo-Delgado, Vanessa, editor, and Kawamoto, André Luiz Satoshi, editor

Published
2021
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14. Breastfeeding and Caries. A Relationship Analysis to Develop a Computer-Assisted Diagnosis Using Random Forest

Author

Zanella-Calzada, Laura A., Galván-Tejada, Carlos E., Chávez-Lamas, Nubia M., Villagrana-Bañuelos, Karen E., Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Roman-Rangel, Edgar, editor, Kuri-Morales, Ángel Fernando, editor, Martínez-Trinidad, José Francisco, editor, Carrasco-Ochoa, Jesús Ariel, editor, and Olvera-López, José Arturo, editor

Published
2021
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15. Neural Hierarchical Interpolation for Standardized Precipitation Index Forecasting.

Author

Magallanes-Quintanar, Rafael, Galván-Tejada, Carlos Eric, Galván-Tejada, Jorge Isaac, Gamboa-Rosales, Hamurabi, Méndez-Gallegos, Santiago de Jesús, and García-Domínguez, Antonio

Subjects
ARTIFICIAL neural networks, INDEPENDENT variables, PRECIPITATION forecasting, TIME series analysis, STATISTICAL correlation
Abstract

In the context of climate change, studying changes in rainfall patterns is a crucial area of research, remarkably so in arid and semi-arid regions due to the susceptibility of human activities to extreme events such as droughts. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applies two type of machine learning methods—long short-term memory (LSTM) and Neural Hierarchical Interpolation for Time Series Forecasting (N-HiTS)—to develop and deploy artificial neural network models with the aim of predicting the regional standardized precipitation index (SPI) in four regions of Zacatecas, Mexico. The predictor variables were a set of climatological time series data spanning from 1964 to 2020. The results suggest that the N-HiTS model outperforms the LSTM model in the prediction and forecasting of SPI time series for all regions in terms of performance metrics: the Mean Squared Error, Mean Absolute Error, Coefficient of Determination and ξ correlation coefficient range from 0.0455 to 0.5472, from 0.1696 to 0.6661, from 0.9162 to 0.9684 and from 0.9222 to 0.9368, respectively, for the regions under study. Consequently, the outcomes revealed the successful performance of the N-HiTS models in accurately predicting the SPI across the four examined regions. [ABSTRACT FROM AUTHOR]

Published
2024
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16. Setting Ranges in Potential Biomarkers for Type 2 Diabetes Mellitus Patients Early Detection By Sex—An Approach with Machine Learning Algorithms.

Author

Morgan-Benita, Jorge A., Celaya-Padilla, José M., Luna-García, Huizilopoztli, Galván-Tejada, Carlos E., Cruz, Miguel, Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Sánchez-Reyna, Ana G., Rondon, David, and Villalba-Condori, Klinge O.

Subjects
ARTIFICIAL neural networks, GENDER differences (Sociology), MACHINE learning, TYPE 2 diabetes, DIASTOLIC blood pressure
Abstract

Type 2 diabetes mellitus (T2DM) is one of the most common metabolic diseases in the world and poses a significant public health challenge. Early detection and management of this metabolic disorder is crucial to prevent complications and improve outcomes. This paper aims to find core differences in male and female markers to detect T2DM by their clinic and anthropometric features, seeking out ranges in potential biomarkers identified to provide useful information as a pre-diagnostic tool whie excluding glucose-related biomarkers using machine learning (ML) models. We used a dataset containing clinical and anthropometric variables from patients diagnosed with T2DM and patients without TD2M as control. We applied feature selection with three different techniques to identify relevant biomarker models: an improved recursive feature elimination (RFE) evaluating each set from all the features to one feature with the Akaike information criterion (AIC) to find optimal outputs; Least Absolute Shrinkage and Selection Operator (LASSO) with glmnet; and Genetic Algorithms (GA) with GALGO and forward selection (FS) applied to GALGO output. We then used these for comparison with the AIC to measure the performance of each technique and collect the optimal set of global features. Then, an implementation and comparison of five different ML models was carried out to identify the most accurate and interpretable one, considering the following models: logistic regression (LR), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbors (KNN), and nearest centroid (Nearcent). The models were then combined in an ensemble to provide a more robust approximation. The results showed that potential biomarkers such as systolic blood pressure (SBP) and triglycerides are together significantly associated with T2DM. This approach also identified triglycerides, cholesterol, and diastolic blood pressure as biomarkers with differences between male and female actors that have not been previously reported in the literature. The most accurate ML model was selection with RFE and random forest (RF) as the estimator improved with the AIC, which achieved an accuracy of 0.8820. In conclusion, this study demonstrates the potential of ML models in identifying potential biomarkers for early detection of T2DM, excluding glucose-related biomarkers as well as differences between male and female anthropometric and clinic profiles. These findings may help to improve early detection and management of the T2DM by accounting for differences between male and female subjects in terms of anthropometric and clinic profiles, potentially reducing healthcare costs and improving personalized patient attention. Further research is needed to validate these potential biomarkers ranges in other populations and clinical settings. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Auto-Machine-Learning Models for Standardized Precipitation Index Prediction in North–Central Mexico.

Author

Magallanes-Quintanar, Rafael, Galván-Tejada, Carlos E., Galván-Tejada, Jorge Isaac, Gamboa-Rosales, Hamurabi, Méndez-Gallegos, Santiago de Jesús, and García-Domínguez, Antonio

Subjects
ARTIFICIAL neural networks, RAINFALL, WATER shortages, PREDICTION models, AGRICULTURE
Abstract

Certain impacts of climate change could potentially be linked to alterations in rainfall patterns, including shifts in rainfall intensity or drought occurrences. Hence, predicting droughts can provide valuable assistance in mitigating the detrimental consequences associated with water scarcity, particularly in agricultural areas or densely populated urban regions. Employing predictive models to calculate drought indices can be a useful method for the effective characterization of drought conditions. This study applied an Auto-Machine-Learning approach to deploy Artificial Neural Network models, aiming to predict the Standardized Precipitation Index in four regions of Zacatecas, Mexico. Climatological time-series data spanning from 1979 to 2020 were utilized as predictive variables. The best models were found using performance metrics that yielded a Mean Squared Error, Mean Absolute Error, and Coefficient of Determination ranging from 0.0296 to 0.0388, 0.1214 to 0.1355, and 0.9342 to 0.9584, respectively, for the regions under study. As a result, the Auto-Machine-Learning approach successfully developed and tested Artificial Neural Network models that exhibited notable predictive capabilities when estimating the monthly Standardized Precipitation Index within the study region. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Classification and selection of the main features for the identification of toxicity in Agaricus and Lepiota with machine learning algorithms

Author

Ortiz-Letechipia, Jacqueline S., primary, Galvan-Tejada, Carlos E., additional, Galván-Tejada, Jorge I., additional, Soto-Murillo, Manuel A., additional, Acosta-Cruz, Erika, additional, Gamboa-Rosales, Hamurabi, additional, Celaya Padilla, José María, additional, and Luna-García, Huizilopoztli, additional

Published
2024
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20. Autonomous Driving: Obtaining Direction Commands by Classifying Images Within a Simulation Platform

Author

de la Torre, Mario Iván Oliva, Luna-García, Huizilopoztli, Celaya-Padilla, José M., Gamboa-Rosales, Hamurabi, Sarmiento, Wilson J., Collazos, Cesar A., Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Agredo-Delgado, Vanessa, editor, Ruiz, Pablo H., editor, and Villalba-Condori, Klinge Orlando, editor

Published
2020
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21. Implementation of Novel Technologies and CAD Software to the Improve and Reduce of Costs in Orthotics Adaptation

Author

Nava-Vázquez, Isaac F., de Avila-Armenta, Eduardo, Espinoza-Bermúdez, Lorena, Esquivel-Cordero, Estefani, Chora-López, Viviana, Galván-Tejada, Jorge I., Galván-Tejada, Carlos E., Gamboa-Rosales, Hamurabi, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, González Díaz, César A., editor, Chapa González, Christian, editor, Laciar Leber, Eric, editor, Vélez, Hugo A., editor, Puente, Norma P., editor, Flores, Dora-Luz, editor, Andrade, Adriano O., editor, Galván, Héctor A., editor, Martínez, Fabiola, editor, García, Renato, editor, Trujillo, Citlalli J., editor, and Mejía, Aldo R., editor

Published
2020
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22. Evaluation of Linked Determinants Between Diabetes and Caries

Author

Chavez-Lamas, Nubia M., Zanella-Calzada, Laura A., Galván-Tejada, Carlos Eric, Gamboa-Rosales, Hamurabi, Galván-Tejada, Jorge I., Celaya-Padilla, José M., Luna-García, Huizilopoztli, Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, González Díaz, César A., editor, Chapa González, Christian, editor, Laciar Leber, Eric, editor, Vélez, Hugo A., editor, Puente, Norma P., editor, Flores, Dora-Luz, editor, Andrade, Adriano O., editor, Galván, Héctor A., editor, Martínez, Fabiola, editor, García, Renato, editor, Trujillo, Citlalli J., editor, and Mejía, Aldo R., editor

Published
2020
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23. Classification of Heart Health by LPC and MFCC Coefficients and Statistical Features

Author

Soto-Murillo, Manuel A., Villagrana Bañuelos, Karen E., Rodriguez-Ruiz, Julieta G., Salinas-González, Jared D., Galván-Tejada, Carlos E., Gamboa-Rosales, Hamurabi, Galván-Tejada, Jorge I., Magjarevic, Ratko, Series Editor, Ładyżyński, Piotr, Associate Editor, Ibrahim, Fatimah, Associate Editor, Lackovic, Igor, Associate Editor, Rock, Emilio Sacristan, Associate Editor, González Díaz, César A., editor, Chapa González, Christian, editor, Laciar Leber, Eric, editor, Vélez, Hugo A., editor, Puente, Norma P., editor, Flores, Dora-Luz, editor, Andrade, Adriano O., editor, Galván, Héctor A., editor, Martínez, Fabiola, editor, García, Renato, editor, Trujillo, Citlalli J., editor, and Mejía, Aldo R., editor

Published
2020
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24. Alcohol Detection in a Car’s Cab Using MQ3 and First Approaches to Sensing: Laboratory Tests

Author

Romero-González, Jonathan Samuel, Luna-García, Huizilopoztli, Celaya-Padilla, José M., Gamboa-Rosales, Hamurabi, Galván-Tejada, Jorge I., Galván-Tejada, Carlos E., Arceo-Olague, José G., Solís-Robles, Roberto, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Ruiz, Pablo H., editor, and Agredo-Delgado, Vanessa, editor

Published
2019
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25. Prevention of Diabetes Mellitus Through the Use of Mobile Technology (mHealth): Case Study

Author

Guerrero-Flores, M. Hazael, Luna-García, Huizilopoztli, Galván-Tejada, Carlos E., Gamboa-Rosales, Hamurabi, Celaya-Padilla, José M., Galván-Tejada, Jorge I., Mendoza-González, Alfredo, Alcala-Rmz, Vanessa, Valladares-Salgado, Adan, Cruz, Miguel, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Ruiz, Pablo H., editor, and Agredo-Delgado, Vanessa, editor

Published
2019
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26. Children Detection on Passenger Seat Using UCD and IDP: An Initial Prototype

Author

Almaraz, William Castañeda, Luna-García, Huizilopoztli, Celaya-Padilla, José M., Gamboa-Rosales, Hamurabi, Mendoza-González, Ricardo, Galván-Tejada, Jorge I., Galván-Tejada, Carlos E., Lozano-Aguilar, Joyce S. A., Solís-Robles, Roberto, Barbosa, Simone Diniz Junqueira, Editorial Board Member, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Ruiz, Pablo H., editor, and Agredo-Delgado, Vanessa, editor

Published
2019
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27. An Empiric Study of the Use of Mobile Technology by Users with Intellectual Disability

Author

Mendoza-González, Alfredo, Luna-García, Huizilopoztli, Mendoza-González, Ricardo, Rusu, Cristian, Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Arceo-Olague, José G., Celaya-Padilla, José M., Solis-Robles, Roberto, Barbosa, Simone Diniz Junqueira, Series Editor, Filipe, Joaquim, Series Editor, Kotenko, Igor, Series Editor, Sivalingam, Krishna M., Series Editor, Washio, Takashi, Series Editor, Yuan, Junsong, Series Editor, Zhou, Lizhu, Series Editor, Ghosh, Ashish, Series Editor, Agredo-Delgado, Vanessa, editor, and Ruiz, Pablo H., editor

Published
2019
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28. Detection of Pedestrians in Reverse Camera Using Multimodal Convolutional Neural Networks

Author

Reveles-Gómez, Luis C., primary, Luna-García, Huizilopoztli, additional, Celaya-Padilla, José M., additional, Barría-Huidobro, Cristian, additional, Gamboa-Rosales, Hamurabi, additional, Solís-Robles, Roberto, additional, Arceo-Olague, José G., additional, Galván-Tejada, Jorge I., additional, Galván-Tejada, Carlos E., additional, Rondon, David, additional, and Villalba-Condori, Klinge O., additional

Published
2023
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29. Redesigning the User Interface of a Learning Platform for Social Engineering Integrating Web Accessibility Basics

Author

Arceo-Olague, José Guadalupe, primary, Ortiz-Reyes, Jorge, additional, Solís-Robles, Roberto, additional, Luna-García, Huizilopoztli, additional, Ordaz-García, Oscar Osvaldo, additional, Gamboa-Rosales, Hamurabi, additional, Galván-Tejada, Carlos Eric, additional, Galván-Tejada, Jorge Issac, additional, Celaya-Padilla, José María, additional, and Ortiz-López, Manuel Agustín, additional

Published
2020
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33. Contralateral asymmetry for breast cancer detection: A CADx approach

Author

Celaya-Padilla, Jose M., Guzmán-Valdivia, Cesar H., Galván-Tejada, Carlos E., Galván-Tejada, Jorge I., Gamboa-Rosales, Hamurabi, Garza-Veloz, Idalia, Martinez-Fierro, Margarita L., Cid-Báez, Miguel A., Martinez-Torteya, Antonio, Martinez-Ruiz, Francisco J., Luna-García, Huizilopoztli, Moreno-Baez, Arturo, and Nandal, Amita

Published
2018
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36. Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network

Author

Mercado Reyna, Jaime, primary, Luna-Garcia, Huizilopoztli, additional, Espino-Salinas, Carlos H., additional, Celaya-Padilla, José M., additional, Gamboa-Rosales, Hamurabi, additional, Galván-Tejada, Jorge I., additional, Galván-Tejada, Carlos E., additional, Solís Robles, Roberto, additional, Rondon, David, additional, and Villalba-Condori, Klinge Orlando, additional

Published
2023
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40. Driver Identification Using Statistical Features of Motor Activity and Genetic Algorithms

Author

Espino-Salinas, Carlos H., primary, Luna-García, Huizilopoztli, additional, Celaya-Padilla, José M., additional, Morgan-Benita, Jorge A., additional, Vera-Vasquez, Cesar, additional, Sarmiento, Wilson J., additional, Galván-Tejada, Carlos E., additional, Galván-Tejada, Jorge I., additional, Gamboa-Rosales, Hamurabi, additional, and Villalba-Condori, Klinge Orlando, additional

Published
2023
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41. COVID-19 outcome prediction by integrating clinical and metabolic data using machine learning algorithms

Author

Villagrana-Bañuelos, Karen E., primary, Maeda-Gutiérrez, Valeria, additional, Alcalá-Rmz, Vanessa, additional, Oropeza-Valdez, Juan J., additional, Herrera-Van Oostdam, Ana S., additional, Castañeda-Delgado, Julio E., additional, Adrián López, Jesús, additional, Borrego Moreno, Juan C., additional, Galván-Tejada, Carlos E., additional, Galván-Tejeda, Jorge I., additional, Gamboa-Rosales, Hamurabi, additional, Luna-García, Huizilopoztli, additional, Celaya-Padilla, José M., additional, and López-Hernández, Yamilé, additional

Published
2022
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43. Metabolomic Selection in the Progression of Type 2 Diabetes Mellitus: A Genetic Algorithm Approach

Author

Morgan-Benita, Jorge, primary, Sánchez-Reyna, Ana G., additional, Espino-Salinas, Carlos H., additional, Oropeza-Valdez, Juan José, additional, Luna-García, Huizilopoztli, additional, Galván-Tejada, Carlos E., additional, Galván-Tejada, Jorge I., additional, Gamboa-Rosales, Hamurabi, additional, Enciso-Moreno, Jose Antonio, additional, and Celaya-Padilla, José, additional

Published
2022
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