Process Research Group
                                  Bluetooth
Mechatronics,
Signal Processing, Control and Artificial Neural Networks
Department of Information and communications technologies
Technological Centre Ceit /“Researching Today, Creating the Future” 
   
 
   
Pattern Recognition
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Pattern recognition is one of the beneficial fields when we consider the development of adaptive methodologies, because of its multiple applications in several knowledge areas. Development of new mathematical models stimulates the research community to creating the new technologies for recognizing behavioral patterns in chaotic systems applied to diagnosing various types of diseases such as: Parkinson’s, cancer, lung and heart disease, to name a few [1].
 
In several cases it is necessary to use vision systems, since the components that are analyzed can present defects which are not visible to the human eye; so it is necessary to implement technologies to improve processes and subprocesses, such as the inspection and classification of parts, which contain some damage or a specific characteristic, for example, such as a small scratch [2].
 
AdaptiveMethodologyDQNU
Variability markers visualization of D-QNU [3]
 
 
Pattern recognition for industrial applications
 
RecognitionProcess
Architecture of the project [2]
 
 
Bsc. Thesis
Student: Erick Antonio Ramos
120610 [1]
 
 
pcolorblanco1
Test, detection of parts using the mask for each color [2]
Recognition1color                                        RecognitionMultipleColors
Results of 1 color recognition [2] Results of multiple color recognition [2]
 
 
References:
 
[1] S. Cervantes, A. Mexicano, José-Antonio Cervantes, Ricardo Rodriguez, and Jorge Fuentes-Pacheco, Binary Pattern Descriptors for Scene Classification. IEEE LATIN AMERICA TRANSACTIONS, VOL. 18, NO. 1, JANUARY 2020, indexed in JCR, Impact Factor: 0.967.
 
[2] Osslan Osiris Viergara Villegas, Vianey Guadalupe Cruz Sánchez, Humberto de Jesús Ochoa Domínguez, Jorge Luis García-Alcaraz, Ricardo Rodriguez Jorge (2016), "Automatic Defect Detection and Classification of Terminals in a Bussed Electrical Center Using Computer Vision", Handbook of Research on Managerial Strategies for Achieving Optimal Performance in Industrial Processes, IGI Publishing Hershey, PA, USA ©2016, May 2016, pp. 241-266, DOI: 10.4018/978-1-5225-0130-5, ISBN13: 9781522501305.
 
[3] Rodriguez Jorge, R., Bila, J., Mizera-Pietraszko, J., Loya Orduño, R. E., Martinez Garcia, E., & Torres Córdoba, R. (2017). Adaptive methodology for designing a predictive model of cardiac arrhythmia symptoms based on cubic neural unit. In Frontiers in Artificial Intelligence and Applications (Vol. 295, pp. 232–239). IOS Press. https://doi.org/10.3233/978-1-61499-773-3-232
 
[4] Bachelor Thesis: “Implementation of an artificial vision system for validation of parts in the industry,” by the student Erick Antonio Ramos Vargas, to get the title of Engineer in Mechatronics. Mechatronics Program. Autonomous University of Ciudad Juárez. Dec 2017. (Advisor: Dr. Ricardo Rodriguez Jorge).
 
[5] Herrera, José Elías Cancino, Ricardo Rodríguez Jorge, Osslan Osiris Vergara Villegas, Vianey Guadalupe Cruz Sánchez, Jiri Bila, Manuel de Jesús Nandayapa Alfaro, Israel U. Ponce, Ángel Israel Soto Marrufo, and Ángel Flores Abad. 2016. “Monitoring of Cardiac Arrhythmia Patterns by Adaptive Analysis.” In , 885–94. doi:10.1007/978-3-319-49109-7_86.
 
[6] S. Cervantes, A. Mexicano, José-Antonio Cervantes, Ricardo Rodriguez, and Jorge Fuentes-Pacheco, Binary Pattern Descriptors for Scene Classification. IEEE LATIN AMERICA TRANSACTIONS, VOL. 18, NO. 1, JANUARY 2020, indexed in JCR, Impact Factor: 0.804.
 
[7] Mexicano, Adriana; Rodriguez Jorge, Ricardo, et al. "Acceleration of the K-Means algorithm by removing stable items", Int. J. of Space-Based and Situated Computing (IJSSC), Vol. 7, No. 2, 2017.
 
[8] Mexicano-Santoyo, A.; Rodriguez-Jorge, Ricardo; Abrego, A., Jiménez; Zúñiga-Treviño; MartínezGarcía, Edgar. A.,Visual Analysis of Differential Evolution Algorithms, Proceedings of the 11th International Conference MISSI 2018. (Web of Science, Proceedings Citation Index).
 
[9] Rodriguez Jorge, Ricardo; Bila, Jiri; Mizera-Pietraszko, Jolanta; Martinez-Garcia, Edgar A., Weight Adaptation Stability of Linear and Higher-Order Neural Units for Prediction Applications, Proceedings of the 11th International Conference MISSI 2018.(Web of Science, Proceedings Citation Index)
 
[10] Mizera-Pietraszko, Jolanta; Kołaczek, Grzegorz; Rodriguez Jorge, Ricardo, Source-Target Mapping Model of Streaming Data Flow for Machine Translation, INnovations in Intelligent SysTems and Applications (INISTA), 2017 IEEE International Conference on, 3-5 July 2017, Gdynia, Poland. (IEEE Xplore, Web of Science Core Collection Database).
 
[11] Rodriguez Jorge, Ricardo, Artificial Neural Networks: Challenges in Science and Engineering Applications, Proceedings of 8th International Conference on Applications of Digital Information and Web Technologies 2017, Ciudad Juarez, Chihuahua, Mexico.
 
[12] Mexicano, A; Cervantes, S.; Rodríguez, R.; Pérez, J.; Almanza, N., "Identifying stable objects for accelerating the classification phase of k-means," 2016 11th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), November 2016, Asan, Korea.
 
[13] Mexicano A., Rodriguez R., Cervantes S., Montes P., Jimenez M., "The Early Stop Heuristic: A new convergence criterion for k-means," Symposium on Optimization Algorithms for Discrete Problems”, ICNAAM 2015, September 2015, Rhodes, Greece (Indexed in ISI web of knowledge, Scopus).