Anabel Martin-Gonzalez

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Ph.D. Anabel Martin-Gonzalez

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Computational Learning & Imaging Reserach (CLIR)
Assistant Profesor at Facultad de Matemáticas 
Universidad Autónoma de Yucatán
Periférico Norte, Merida, Mexico.

Tel. y Fax: (999) 942 31 40 ext. 1129


Education and Awards

  • 2011: Ph.D. in Computer Science with Magna Cum Laude at TECHNISCHE UNIVERSITAET MUENCHEN (TUM), Germany, in the Chair of Computer Aided Medical Procedures (CAMP), "Advanced Imaging in Head-Mounted Displays for Patients with Age-Related Macular Degeneration".

  • 2006: Master in Computer Science at UNIVERSIDAD NACIONAL AUTONOMA DE MEXICO (UNAM), Mexico, "Sistema de clasificación de imágenes de microtornillos basado en una red neuronal artificial". Received the Alfonso Caso's Medal for outstanding academic performance.

  • 2004: Bachelor in Computer Science at UNIVERSIDAD AUTONOMA DE YUCATAN (UADY), Mexico, "Desarrollo de un sistema de cómputo para el análisis de imágenes, identificación y reconstrucción tridimensional de neuronas en el núcleo pedúnculo pontino del cerebro de ratas".

  • Membership to the National System of Researchers in Mexico since 2015, current level "Candidate".

Research Interests

  • Pattern Recognition in Images
  • Machine Learning
  • Augmented Reality

Research Projects


Chagas Parasite Segmentation

Chagas disease is a tropical parasitic disease caused by the protist Trypanosoma cruzi. About 7 million to 8 million people worldwide, mostly in Latin America, are estimated to be infected. Since blood samples analisys is time consuming, this project proposes automated systems based on convolutional neural networks to detect this parasite.

Comet Assay Segmentation

The comet assay (single-cell gel electrophoresis) has been a reliable method for the study of DNA damage of the cells and the evaluation of their regenerative capacity, playing an important role for the analisys of degenerative diseases (cancer, diabetes, osteoporosis, etc.). This project proposes automatic segmentation methods to extract the DNA cells from comet assay images and to study their degradation.


Online Speaker Diarization

Speaker diarization is the process of partitioning the speech signal in order to group speech segments corresponding to the same speaker. This research proposes an online speaker diarization system using deep learning techniques.


Traffic Signal Recognition

The recognition of traffic signals is one of the fundamental tasks in the advanced driving assistance systems, since most of the actions the vehicle must take to maintain a safe and convenient driving fall on them. The project implements a deep learning algorithm (YOLO) to classify and detect traffic signals from the Yucatan state.

Lunar Crater Detection

The identification of craters on the lunar surface is high scientific interest for to obtain relevant information about the periods of meteoric incidence in the solar system. In this project, we propose machine learning methods to detect craters from images of the lunar surface.

Mexican Sign Language Recognition using Machine Learning

A sign language is an effective means of communication that provides the deaf a way to interact with the world around them. Implementation of machine learning techniques to develop a sign language translator may help to bridge the gap between those who can hear and those who cannot.

Sign Recognition for Service Robots Communication

Service robots are aimed to assist people in daily life task. In this project, we develop different body-gestures recognition techniques to interact with service robots.

Euclidean Vectors Education using Augmented Reality

Augmented reality is one of the emerging technologies that has demonstrated to be an efficient technological tool to enhance learning techniques. In this project, we developed an augmented reality system for teaching Euclidean vectors in physics and mathematics. The goal of this pedagogical tool is to facilitate user’s understanding of physical concepts, such as magnitude, direction, and orientation, together with basic vector-related operations like addition, subtraction and cross product.

Iris Recognition based on Machine Learning Techniques

Biometrics is a discipline that studies methods for verification and identification of individuals based on physical or behavioral characteristics of a person. The iris of the human eye is a structure which can be used as a reliable feature to identify individuals since its intrinsic pattern is considered unique and permanent for each individual. In this project, an iris recognition system is proposed based on speeded up robust features (SURF) matching statistics which feed a learning algorithm to automatically decide whether the two images correspond to the same iris. Experiments performed on CASIA iris image database show that our method has promising capabilities for iris recognition.

Journal Publications

  • A Mean Curvature Regularized BasedModel for Demodulating PhaseMaps from Fringe Patterns (ISSN: 1815-2406), Carlos Brito-Loeza, Ricardo Legarda-Sáenz, Arturo Espinosa-Romero, Anabel Martin-Gonzalez, Communications in Computational Physics, Vol. 24, No. 1, Pag. 27-43, 2018.

  • Mexican Sign Language Alphanumerical Gestures Recognition using 3D Haar-like Features (ISSN: 1548-0992), J. Jimenez, A. Martin, V. Uc and A. Espinosa, IEEE Latin America Transactions, Vol. 15, No. 10, Pag. 2000-2005, 2017.

  • Body Gestures Recognition System to Control a Service Robot (ISSN: 2074-9007), José L. Medina Catzin, Anabel Martin-Gonzalez, Carlos Brito-Loeza, Victor Uc-Cetina, International Journal of Information Technology and Computer Science, Vol. 9, Pag. 69-76, 2017.

  • Usability evaluation of an augmented reality system for teaching Euclidean vectors (ISSN: 1470-3297), Anabel Martin-Gonzalez, Angel Chi-Poot, Victor Uc-Cetina, Innovations in Education and Teaching International, Vol. 53, Num. 6, Pag.627-636, 2016.

  • Aprendizaje de vectores Euclidianos utilizando un sistema de realidad aumentada (ISSN:1870-4069), Angel Chi-Poot, Anabel Martin-Gonzalez, Victor Menendez-Dominguez, Arturo Espinosa-Romero, Research in Computing Science, Vol. 89, Pag. 9-16, 2015. 

  • A convex set based algorithm to automatically generate Haar-like features (ISSN:2333-9071), César Cobos-May, Víctor Uc-Cetina, Carlos Brito-Loeza and Anabel Martin-Gonzalez, Computer Science and Applications, Vol.2, Pag.64-70, 2015.

  • Introducción a técnicas de reconocimiento de iris (ISSN:2007-2635), Edgar Israel Hernandez-Garcia, Anabel Martin-Gonzalez, Carlos Brito-Loeza, Abstraction and Application, Vol.12, Pag.1-18, 2015.

  • Introducción a los métodos variacionales en procesamiento de imágenes: filtros de ruido (ISSN: 2007-2635), Carlos Brito-Loeza, Victor Uc-Cetina, Anabel Martin-Gonzalez, Abstraction and Application, Vol.10, Pag.19-34, 2014.

  • Mediated reality magnification for macular degeneration rehabilitation (ISSN:0950-0340), Anabel Martin-Gonzalez, Konstantin Kotliar, Jorge Rios-Martinez, Ines Lanzl, Nassir Navab, Journal of Modern Optics, Vol.61, Pag.1400-1408, 2014.

  • Improved neural classifier for microscrew shape recognition (ISSN: 1060-992X), A. Martin-Gonzalez, T. Baidyk, E. Kussul, O. Makeyev, Optical Memory and Neural Networks (Information Optics), Vol.19, Pag.220-226, 2010.

  • Head-mounted virtual loupe with sigth-based activation for surgical applications, A. Martin-Gonzalez, S. M. Heining, N. Navab, IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Pag.207-208, Memorias de congresos , 2009.

  • Limited receptive area neural classifier for texture recognition of mechanical treated surfaces (ISSN: 0925-2312), O. Makeyev, E. Sazonov, T. Baidyk, A. Martín, Neurocomputing, Vol.71, Pag.1413-1421, 2009.

  • Permutation coding technique for image recognition systems (ISSN: 1045-9227), Ernst M. Kussul, Tatiana N. Baidyk, Donald C. Wunsch II, Oleksandr Makeyev, Anabel Martín, IEEE Transactions on Neural Networks, Vol.17, Pag.1566-1579, 2006.

Conference Publications

  • Online Breast Cancer Diagnosis System (ISBN: 978-3-319-30446-5), Asad Safi and Anabel Martin-Gonzalez, Communications in Computer and Information Science, Vol.597, Pag.108-115, 2016.

  • Towards and automatic counter of lunar craters,Jesús Cabrera González, Anabel Martin-Gonzalez, Jorge Lugo-Jiménez, Víctor Uc-Cetina, International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Vol. , Pag.282-285, 2014.

  • Simulation and modeling of metamorphopsia with a deformable grid (ISSN:0926-9630), A. Martin-Gonzalez, I. Lanzl, R. Khoramnia, N. Navab, Studies in health technology and informatics, Vol.163, Pag.336-342, 2011.

  • Image recognition systems based on random local descriptors, Ernst Kussul, Tatiana Baidyk, Donald Wunsch, Oleksandr Makeyev, Anabel Martín, IEEE International Joint Conference on Neural Networks, Vol. , Pag. 2415-2420, 2006.


  • Intelligent Computing Systems, Anabel Martin-Gonzalez and Victor Uc-Cetina, SPRINGER, ISBN978-3-319-30446-5, 2016.

Book Chapters

  • Micromechanics as a testbed for artificial intelligence methods evaluation, PROFESSIONAL PRACTICE IN ARTIFICIAL INTELLIGENCE JOHN DEBENHAM, SPRINGER, Vol. 218, Pags. 352, Ernst Kussul, Tatiana Baidyk, Felipe Lara-Rosano, Oleksandr Makeyev, Anabel Martin, Donald Wunsch.

  • Reconocimiento de iris utilizando aprendizaje automático, UNIVERSIDAD JUAREZ AUTONOMA DE TABASCO, Walter Jiménez Jiménez, Anabel Martin-Gonzalez, Pags. 8, 2016.

  • Clasificador neuronal para el reconocimiento de imágenes de microtornillos en micromecánica, CCADET, Tetyana Baydyk, Ernst Kussul, Anabel Martín, Pags. 18, 2007.

  • Reconocimiento de imágenes en los procesos adaptivos para tarea de corte en micromáquinas herramienta, CCADET, Tetyana Baydyk, Ernst Kussul, Anabel Martín, Pags. 21, 2004.


  1. Sistema de realidad aumentada para apoyar la enseñanza de operaciones vectoriales, Encuentro Mexicano de Realidad Aumentada, ANGEL CHI-POOT, México, 2015.

  2. Euclidean vectors in physics education using augmented reality, International Conference on Augmented and Virtual Reality, A. CHI-POOT, Italia, 2014.

  3. Towards an automatic counter of lunar craters, International Conference on Electrical Engineering, Computing Science and Automatic Control, V. UC-CETINA J. LUGO-JIMENEZ J. CABRERA GONZALEZ, México, 2014.

  4. Evaluation of hybrid magnification for AMD patients with an eye-tracking based simulation system, The Association for Research in Vision and Ophthalmology, Inc. (ARVO) (Annual Meeting), INEZ LANZL RAMIN KHORAMNIA NASSIR NAVAB, Estados Unidos, 2011.

  5. Sight-based magnification system for surgical applications, Bildverarbeitung für die Medizin (BVM), SANDRO HEINING, NASSIR NAVAB, Alemania, 2010.

  6. System for modeling and localizing metamorphosia in octimages, The Association for Research in Vision and Ophthalmology, Inc. (ARVO) (Annual Meeting), INES LANZL, RAMIN KHORAMNIA, NASSIR NAVAB, Estados Unidos , 2010.

  7. Real time hybrid magnification system for AMD patients, The Association for Research in Vision and Ophthalmology, Inc. (ARVO) (Annual Meeting), INES LANZL, KONSTANTIN KOTLIAR, NASSIR NAVAB, Estados Unidos, 2009.

  8. Neural classifier for microscrew shape recognition in micromechanics, XXXII CLEI Latin America Conference on Informatics, TETYANA BAYDYK, Chile , 2006.

  9. Reconocimiento de texturas de superficies metálicas, Nacional, SOMI XX Congreso de Instrumentación, OLEKSANDR MAKEYEV, TETYANA BAYDYK, ERNST KUSSUL, México, 2005.

  10. Método de alineamiento de imágenes de cortes histológicos elásticos deformados del núcleo pedúnculo pontino del cerebro de ratas, XVII Congreso Nacional y III Congreso Internacional de Informática y Computación de la ANIEI 2004, ARTURO ESPINOSA ROMERO, México, 2004.

  11. Problemas en los procesos adaptivos para tareas de corte en micromáquinas herramienta, SOMI XIX Congreso de Instrumentación, TETYANA BAYDYK, ERNST KUSSUL, México, 2004.

  12. Diseño y construcción de un brazo robótico de tres grados de libertad controlado desde una computadora PC 3er. Congreso Estudiantil de Computación CORE 2002, KAREN NAVARRETE KAO JESÚS BOTE MAY, México, 2002.

  13. Diseño y construcción de un sistema de telemetría para el registro de potenciales de acción muliunitarios, SOMI XVII Congreso de Instrumentación, FRANCISCO HEREDIA LÓPEZ FERNANDO ÁLVAREZ CERVERA, México, 2002.

  14. Interfaces con el mundo real, Nacional, 2° Congreso de Ciencias de la Computación, KAREN NAVARRETE KAO, JESÚS BOTE MAY, México,  2001.

Completed Theses

  • Análisis computacional de células procesadas por electroforesis en gel (ensayo cometa), Javier Luna González, 2018

  • Clasificación morfométrica de tumores cerebrales utilizando aprendizaje supervisado, Angel Carrillo Bermejo, 2018

  • Auto-organización de vehículos no tripulados para recorrer una superficie utilizando aprendizaje por refuerzo, Gian N. Cuello Nicholson, 2018

  • Implementación de un sistema de navegación cinética satelital para asistir en el control de posición de vehículos aéreos no tripulados, Alex Turriza Suárez, 2017.

  • Interfaz interactiva basada en el reconocimiento de gestos corporales para controlar un robot de servicio, José Luis Medina Catzin, 2017.

  • Implementacion de hardware para la segmentacion de iris, Kenny Canto Magaña, 2016.

  • Reconocimiento de señas de las manos a través de técnicas de aprendizaje automático, Javier Jiménez Villafaña, 2016.

  • Detección de cráteres lunares con técnicas de aprendizaje automático, Jesús Cabrera González, 2016.

  • Sistema de realidad aumentada para la enseñanza de vectores euclidianos, Angel de Jesús Chi Poot, 2015.

  • Reconocimiento de iris aplicando técnicas de aprendizaje automático, Edgar Israel Hernández García, 2015.