Academic Positions

  • Present 2015

    Associate Professor with Habilitation

    University of Porto, Faculty of Engineering

  • 2015 2014

    Assistant Professor with Habilitation

    University of Porto, Faculty of Engineering

  • 2014 2009

    Assistant Professor

    University of Porto, Faculty of Engineering

  • 2009 2006

    Invited Assistant Professor

    University of Porto, Faculty of Engineering

Education & Training

  • Ph.D. 2006

    Ph.D. in ECE (Computer Vision)

    University of Porto, Faculty of Engineering

    Title of the thesis: "Metadata Assisted Image Segmentation"

  • MSc.2005

    Master in Mathematical Engineering

    University of Porto, Faculty of Sciences

  • B.A.1999

    Licentiate (5-year Licenciatura) in ECE

    University of Porto, Faculty of Engineering

Research Lines

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    Breast Cancer Screening and Diagnosis

    Through the years, several CAD systems have been developed to help radiologists in the hard task of detecting signs of cancer in the numerous screening mammograms. A more recent trend includes the development of pre-CAD systems aiming at identifying normal mammograms instead of detecting suspicious ones. Normal breasts are screened-out from the process, leaving radiologists more time to focus on more difficult cases. We are interested in learning interpretable models for pre-CAD from weakly annotated data, both from mammograms and tomosynthesis.

    Screening mammography is performed in the asymptomatic population to detect early signs of breast cancer such as masses, microcalcifications (MCs), bilateral asymmetry and architectural distortions (AD). Diagnostic mammography is performed on patients who have already demonstrated abnormal clinical findings. Both screening and diagnostic mammography are performed by radiologists who visually inspect mammograms. This is not an easy task: mammograms generally have low contrast. Mammograms show normal structures such as fat, fibroglandular tissue, breast ducts and nipples, as well as possible abnormalities. Although fat appears as black regions on mammograms, everything else appear as levels of white, making it hard to distinguish between normal and abnormal tissue.

    The assumption made in this work is that, in screening, a substantial proportion of normal cases can be automatically detected, alleviating the human effort and giving the specialist more time to carefully evaluate more ambiguous cases.

    We are interested in learning interpretable models for pre-CAD from weakly annotated data, both from mammograms and using the more recent tomosynthesis exam. For diagnosis, we aim at support the decision process by develping tools to identify clinically relevant findings.

  • image

    Breast Cancer Surgery Planning and Evaluation

    The overall aim of this research line is to improve the Quality Of Life (QOL) of breast cancer surgery patients (BCSP) - patients submitted to loco-regional treatment (surgery and radiation therapy whenever needed), through the development of objective tools for evaluating their aesthetic outcome and related QOL and as consequence to measure the quality of treatment and push the standards to a higher level.

    When a woman faces a breast cancer diagnosis, and surgery is proposed, several options are available. The decision as to which type of surgery to offer patients is largely subjective and based almost exclusively on the judgment and experience of the clinician. The cosmetic outcome of surgery is a function of many factors including tumour size and location, the volume of the breast, its density, and the dose and distribution of radiotherapy. In breast-conserving surgery, there is evidence that approximately 30% of women receive a suboptimal or poor aesthetic outcome, however there is currently no standardised method of identifying these women.

    In surgery planning, we aim to provide objective tools, tailored to the individual patient, to predict the aesthetic outcome of breast conserving surgery.

    After the surgery, we aim to objectively evaluate the aesthetic outcome of the procedure.

    The capability of (automatically) evaluating the aesthetic result depends strongly on our understanding of the main factors contributing to that outcome. Therefore, we study and identify the factors relevant to the aesthetic evaluation and perception of the result of the surgical and radiation therapy procedure. These will be the factors that can be derived from patients, tumour and treatment data and also from objective features extracted from digital photographs and 3D meshes of the breast surface. In spite of the differences between the available surgical and radiation therapy procedures, they share similarities that can be exploited when developing methods specific to each treatment type. The individual factors can be combined to provide an overall assessment of the aesthetic result. We adopt transfer and multitask learning techniques from the machine learning community to leverage the learning of models specific to each treatment type.

  • image

    Cervical Cancer Screening

    Cervical cancer is one of the leading causes of cancer death in women, with most cases occurring in low to middle income countries. Screening tests such as cytology or colposcopy have been responsible for a strong decrease in cervical cancer deaths. In this research line we aim to achieve results that exceed the current state-of-the-art in cervical cancer screening and diagnosis, in colposcopy procedures, by creating a Computer Aided-Diagnosis (CADx) system that can be easily integrated in the conventional clinical workflow.

    Cervical cancer is one of the leading causes of cancer death in women, with most cases occurring in low to middle income countries. Screening tests such as cytology or colposcopy have been responsible for a strong decrease in cervical cancer deaths. In this research line we aim to achieve results that exceed the current state-of-the-art in cervical cancer screening and diagnosis, in colposcopy procedures, by creating a Computer Aided-Diagnosis (CADx) system that can be easily integrated in the conventional clinical workflow.

    When a new patient arrives at the clinical consultation, a cytology, either conventional or Liquid-based Cytology (LBC), depending on the resource availability, is performed. Cytological testing involves collecting exfoliated cells from the cervix, which are stained, fixated, and then visually examined under a microscope by a cytotechnologist. Despite being recommended by the World Health Organization (WHO), this procedure has the disadvantage of requiring great resources in terms of quality control, training and time consumption. If the cytology reveals any suspicious findings, a colposcopy is done, which consists in a common and low cost diagnosis method for the visualization of the affected area using a colposcope. The WHO recommends a protocol to perform the diagnosis which includes the examination using different lens filters and applying several solutions sequentially, which gives different sources of data. Since the manual evaluation is highly error prone, some projects have attempted the automatic detection but with limited performance and including only data from part of the protocol.

    The purpose of this research line is to achieve results that exceed the current state-of-the-art in cervical cancer screening and diagnosis, in colposcopy procedures, by creating a Computer Aided-Diagnosis (CADx) system that can be easily integrated in the conventional clinical workflow. The primary goals of the project include the exploration of low-cost image acquisition approaches for cervical data; quality assessment of cervical imaging; image processing and analysis of cytological and colposcopy data; and fundamental machine learning and computer vision strategies to take advantage of multimodal settings with interpretability requirements.

  • image

    Unconstrained Biometrics

    Very short description of the project.

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    Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

    Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

  • image

    Machine Learning

    Very short description of the project.

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    Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

    Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Students

PhD Students

  • Anisa Allahdadi, PhD St. FEUP (co-supervisor), "to be defined", 2012/xxxx
  • Hooshiar Zolfagharnasab, PhD St. FEUP (co-supervisor), "to be defined", 2012/xxxx
  • Luis Rosado, PhD St. FEUP (supervisor), "to be defined", 2013/xxxx
  • Kelwin Fernandes, PhD St. FEUP (supervisor), "to be defined", 2014/xxxx
  • Pedro Ferreira, PhD St. FEUP (co-supervisor), "to be defined", 2015/xxxx
  • Joana Silva, PhD St. FEUP (supervisor), "to be defined", 2015/xxxx
  • Ricardo Cruz, PhD St. FEUP (supervisor), "to be defined", 2016/xxxx
  • Silvia Bessa, PhD St. FEUP (co-supervisor), "to be defined", 2016/xxxx
  • Ricardo Araujo, PhD St. FEUP (co-supervisor), "to be defined", 2016/xxxx
  • Diogo Pernes, PhD St. FCUP (supervisor), "to be defined", 2017/xxxx
  • Eduardo Dixo, PhD St. FCUP (supervisor), "to be defined", 2017/xxxx
  • Wilson Silva, PhD St. FCUP (supervisor), "to be defined", 2017/xxxx

MSc Students

  • Álvaro Ferreira
  • Vanessa Penso
  • Licínio Oliveira
  • Filipa Castro
  • Filipe Marques
  • Ricardo Cerqueira
  • José Rebelo
  • Joni Gonçalves
  • Guilherme Santos

Alumini Students

PhD Students

  1. Joao C. Monteiro, PhD St. FEUP (supervisor), "Multimodal Biometric Recognition Under Unconstrained Settings", 2012/2017
  2. Samaneh Khoshrou, PhD St. FEUP (supervisor), "Learning in Evolving Video Streams", 2011/2017
  3. Chetak Kandaswamy, PhD St. FEUP (supervisor), "Contributions on Deep Transfer Learning", 2013/2016
  4. Eduardo José Marques Pereira, PhD St. FEUP (supervisor), "Humans in Action at Different Levels: the group, the whole and the parts", 2011/2016
  5. Ana Filipa Pinheiro Sequeira, PhD St. FEUP (supervisor), "Liveness Detection and Robust Recognition in Iris and Fingerprint Biometric Systems", 2011/2015
  6. Ines Campos Monteiro Sabino Domingues, PhD St. FEUP (supervisor), "An automatic mammogram system: from screening to diagnosis", 2009/2015
  7. Andre Miguel Passos Baltazar, PhD St. Escola das Artes, Univ. Catolica (co-supervisor), "Zatlab: Recognizing gestures for artistic performance interaction", 2009-2015
  8. Helder Filipe Pinto de Oliveira, PhD St. FEUP (supervisor), "An Affordable and Practical 3D Solution for the Aesthetic Evaluation of Breast Cancer Conservative Treatment", 2008/2013
  9. Ana Maria Silva Rebelo, PhD St. FEUP (supervisor), "Robust Optical Recognition of Handwritten Musical Scores based on Domain Knowledge", 2008/2012
  10. Ricardo Jorge Gamelas de Sousa, PhD St. FEUP (supervisor), "Multicriteria learning on ordinal data", 2008/2012
  11. Pedro Miguel Machado Soares Carvalho, PhD St. FEUP (co-supervisor), "Video Object Tracking - Contributions to Object Description and Performance Assessment", 2007-2012

MSc Students

  1. Tiago Salgado Magalhães Taveira-Gomes, MSc St. FEUP (supervisor), "Reinforcement Learning for Primary Care Appointment Scheduling", 2017
  2. Borgine Vasques Gurue, MSc St. FEUP (supervisor), "Analise e Classificacao de Imagem Hiper-espectral", 2017
  3. Bruno Miguel Ferreira Moreira, MSc St. FEUP (supervisor), "Analise Automatica de Melanoma Utilizando Imagens Dermatoscopicas", 2017
  4. Eduardo Meca Castro, MSc St. FEUP (supervisor), "Rotated Filters and Learning Strategies in Convolutional Neural Networks for Mammographic Lesions Detection", 2017
  5. Pedro Guilherme Reis Alves, MSc St. FEUP (supervisor), "Automatic Assessment of Infantile Hemangiomas", 2017
  6. Sofia de Sousa Almeida, MSc St. FEUP (supervisor), "Performance assessment and prediction of football players: Tailoring an architecture with spatiotemporal positional and physiological features", 2017
  7. Claudia Sofia Alferes Ribeiro da Silva Silveira, MSc St. FEUP (supervisor), "Driver's Fatigue State Monitoring using Physiological Signals", 2017
  8. Joao Tiago Ribeiro Pinto, MSc St. FEUP (supervisor), "Continuous Biometric Identification on the Steering Wheel", 2017
  9. Salik Ram Khanal, MSc St. FEUP (supervisor), "Machine Learning for Supermarket Data Analysis", 2016
  10. Tiago Daniel Santos Freitas, MSc St. FEUP (supervisor), "3D Face Recognition Under Unconstrained Settings Using Low-Cost Sensors", 2016
  11. Ricardo Reis Marques Silva, MSc St. FEUP (supervisor), "Measuring Impedance in Congestive Heart Failure", 2016
  12. Rui Cardoso Esteves, MSc St. FEUP (supervisor), "Mobile multimodal biometric identification for african communities", 2015
  13. Ana Filipa Domingues Geros, MSc St. FEUP (co-supervisor), "Capture and analysis of the trajectories of anatomical points on the face to support and evaluate reconstructive plastic surgery", 2015
  14. Hugo Miguel Felgueira de Andrade, MSc St. FEUP (supervisor), "Image processing methodology for blood cell counting via mobile devices", 2015
  15. Pedro Manuel Nunes Sequeira, MSc St. FEUP (supervisor), "Hierarchical Dynamical Systems", 2015
  16. Andre Filipe Ferreira de Castro, MSc St. FEUP (co-supervisor), "Reconhecimento de simbolos musicais em imagens cinza de partituras manuscritas", 2014
  17. Marisa Mendonca dos Reis, MSc St. FCUP (co-supervisor), "A Comparative Study on Fingerprint Matching Algorithms", 2014
  18. Carlos Jorge Alves da Hora Martins, MSc St. FEUP (supervisor), "Contributions to the Automatic Recognition of Portuguese Sign Language", 2014
  19. Filipe Oliveira Ramos Trocado Ferreira, MSc St. FEUP (supervisor), "Video Analysis in Indoor Soccer with a Quadcopter", 2014
  20. Joao David Pereira da Costa, MSc St. FEUP (supervisor), "Ensemble Methods in Ordinal Data Classification", 2014
  21. Ana Rute Caetano Louro, MSc St. FEUP (supervisor), "Liveness Detection in Biometrics", 2014
  22. Ana Rita Carvalho Moreira, MSc St. FEUP (co-supervisor), "Dynamic Analysis of Upper Limbs Movements after Breast Cancer Surgery", 2014
  23. Pedro Miguel Ferro da Costa, MSc St. FEUP (co-supervisor), "Kinect Based System for Breast 3D Reconstruction", 2014
  24. Vitor Joel do Nascimento Araujo, MSc St. FEUP (supervisor), "Human detection solution for a retail store environment", 2014
  25. Rui Miguel Filipe da Silva, MSc St. FEUP (co-supervisor), "Mobile framework for recognition of musical characters", 2013
  26. Joao Paulo Leite Botelho, MSc St. FEUP (supervisor), "KITE - Tracking da bola em jogos de futsal com video", 2013
  27. Juliano Ferreira Jorge Murari, MSc St. FEUP (supervisor), "Deteccao de vivacidade em sistemas de reconhecimento de iris", 2013
  28. Joana Cristina Lopes da Fonseca, MSc St. FEUP (supervisor), "Pre-CADs in Breast Cancer", 2013
  29. Claudia Marina Correia Castro, MSc St. FMUP (supervisor), "Estudo do impacto da densidade mamaria no cancro da mama", 2013
  30. Vitor Hugo Couto Vidal, MSc St. FEUP (supervisor), "Staffline detection and removal in the Grayscale Domain", 2012
  31. Marco Alexandre Dias Silva, MSc St. FEUP (supervisor), "Kinect Based System Applied to Breast Cancer Conservative Treatment", 2012
  32. Joao Pedro da Silva Monteiro, MSc St. FEUP (supervisor), "Automatic Behavior Recognition in Laboratory Animals using Kinect", 2012
  33. Joao Carlos de Sousa Monteiro, MSc St. FEUP (supervisor), "Robust Iris Recognition under Unconstrained Settings", 2012
  34. Miguel Jorge Pereira Cova, MSc St. FEUP (supervisor), "Global localization of vertical road signs using a car equipped with a stereo vision system and GPS", 2011
  35. Diogo Santos Martins, MSc St. FEUP (supervisor), "Biometric recognition based on the texture along palmprint principal lines", 2011
  36. Diogo Machado Carneiro Dias, MSc St. FEUP (supervisor), "Computational Vision Applied to the Segmentation and Morphometric Characterization of the Sciatic Nerve in Microscopic Images", 2011
  37. Joao Miguel Trigo Soares, MSc St. FEUP (supervisor), "Uncalibrated Stereo Vision applied to Breast Cancer Treatment Aesthetic Assessment", 2011
  38. Helder Jose da Silva Matos, MSc St. FEUP (supervisor), "Reconhecimento Biometrico Baseado na Geometria da Mao", 2011
  39. Joao Paulo da Silva Ferreira Monteiro, MSc St. FEUP (supervisor), "Computer Aided Detection in Mammography", 2011
  40. Igor Francisco Areias Amaral, MSc St. FCUP (supervisor), "Content-Based Image Retrieval for Medical Applications", 2010
  41. Jose Graciano Almeida Ramos, MSc St. FEUP (supervisor), "Algoritmos Colaborativos para Sistemas de Recomendacao", 2010
  42. Telmo Tiago Barbosa Pinto, MSc St. FEUP (supervisor), "Music Score Binarization Based on Content Knowledge", 2010
  43. Ezilda Duarte Almeida, MSc St. FEUP (supervisor), "Classificacao Ordinal com Opcao de Rejeicao", 2010
  44. Luis Alberto de Sousa Rangel das Neves, MSc St. FEUP (supervisor), "Sistema Web Semi-automatico para Anotacao Colaborativa de Media H.264 e Flash Video", 2010
  45. Andreas Dieter Mendes Seufert, MSc St. FEUP (supervisor), "Investigacao e Aperfeicoamento de Algoritmos de Reconhecimento de Simbolos Musicais", 2010
  46. Pedro Augusto Fernandes Antunes Martins Vitoriano, MSc St. FEUP (supervisor), "Avaliacao Automatica do Resultado de Intervencoes Cirurgicas", 2010
  47. Rui Alexandre Rodrigues Carneiro, MSc St. FEUP (supervisor), "Unificacao e expansao da interface de pesquisa no webmail", 2009
  48. Marcia dos Santos Pinheiro, MSc St. FEUP (supervisor), "Sistema Web para o Reconhecimento de Partituras Musicais", 2009
  49. Sergio Manuel Colaco de Sa, MSc St. FEUP (co-supervisor), "Adaptacao Preditiva de Conteudo Multimedia", 2009
  50. Andre Miguel Passos Baltazar, MSc St. FEUP (supervisor), "Extraccao de Informacoes Ritmicas de Movimentos de Danca Atraves de um Sinal de Video", 2009
  51. Ricardo Jorge Gamelas de Sousa, MSc St. FCUP (supervisor), "Automatic aesthetic evaluation of breast cancer conservative treatment", 2008
  52. Ana Maria Silva Rebelo, MSc St. FCUP (supervisor), "New methodologies towards an automatic optical recognition of handwritten musical scores", 2008
  53. Pedro Luis Cameira Sollari Allegro, MSc St. FEUP (supervisor), "Singing Voice Detection in Polyphonic Music Signals", 2008
  54. Luis Daniel Torres Rebelo, MSc St. FEUP (supervisor), "Avaliacao objectiva do resultado estetico dos tratamentos do cancro da mama", 2007/2008
  55. Luis Miguel Marques Soeiro Batista, MSc St. FEUP (supervisor), "Sistema automatico de reconhecimento de formularios manuscritos", 2007/2008
  56. Luis Jorge Trindade Certo, MSc St. FEUP (supervisor), "QuidPyx mobile - Sistema de recomendação de musica em dispositivos moveis", 2007/2008
  57. Joao Carlos Loureiro de Jesus Oliveira, MSc St. FEUP (supervisor), "A Smarter YouTube - Sistema de organizacao automatica de video com base no seu conteudo semantico", 2007/2008
  58. Guilherme Artur Conceicao Capela, MSc St. FEUP (supervisor), "Reconhecimento de simbolos musicais manuscritos na framework Gamera", 2008
  59. Filipe Emanuel Amaro Coelho, MSc St. FEUP (supervisor), "Sistema automatico de reconhecimento do montante de um cheque", 2008
  60. Guilherme Artur Conceicao Capela, undergraduate st. FEUP (co-supervisor), "Sistema automatico de reconhecimento de pautas musicais manuscritas" (system design and implementation), 2007
  61. Ana Maria Silva Rebelo, undergraduate st. FCUP (co-supervisor), "Reconhecimento automatico de pautas musicais manuscritas" (algorithm investigation and implementation), 2007
  62. Silvia Maria Faria Saramago, undergraduate st. FEUP (co-supervisor), "Extracção 3D da estrutura da cena e dos parâmetros da câmara", 2003

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Mass Segmentation in Mammograms: a Cross-Sensor comparison of deep and tailored features

Jaime S. Cardoso, Nuno Marques, Neeraj Dhungel, Gustavo Carneiro, Andrew Bradley
Conference Papers Proceedings of the IEEE International Conference on Image Processing (ICIP)

bibtex

@inproceedings{JaimeICIP2017, author = "Jaime S. Cardoso and Nuno Marques and Neeraj Dhungel and Gustavo Carneiro and Andrew Bradley", title = "Mass Segmentation in Mammograms: a Cross-Sensor comparison of deep and tailored features", booktitle = "Proceedings of the IEEE International Conference on Image Processing (ICIP)", url = "http://www.inescporto.pt/~jsc/publications/conferences/2017JaimeICIP.pdf", year = "2017", }.

Deep Learning and Data Labeling for Medical Applications

Gustavo Carneiro, Diana Mateus, Loic Peter, Andrew Bradley, Joao M. R. S. Tavares, Vasileios Belagiannis, Joao Paulo Papa, Jacinto C. Nascimento, Marco Loog, Zhi Lu, Jaime S. Cardoso, Julien Cornebise
Edited bookFirst International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings

bibtex

@book{CardosoMICCAIDLMIA2016, year="2016", title="Deep Learning and Data Labeling for Medical Applications", subtitle = "First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings", volume="10008", editor = "Gustavo Carneiro and Diana Mateus and Loïc Peter and Andrew Bradley and João Manuel R. S. Tavares and Vasileios Belagiannis and João Paulo Papa and Jacinto C. Nascimento and Marco Loog and Zhi Lu and Jaime S. Cardoso and Julien Cornebise" }

Discriminative Directional Classifiers

Kelwin Fernandes, Jaime S. Cardoso
Journal Paper Neurocomputing

bibtex

@article{KelwinNC2016, author = "Kelwin Fernandes and Jaime S. Cardoso", title = "Discriminative Directional Classifiers", journal = "Neurocomputing", year = "2016", type = "article", pages = "141--149", url = "http://www.inescporto.pt/~jsc/publications/journals/2016KelwinNeuroComputing.pdf", }

Robust Iris Localisation in Challenging Scenarios

Joao C. Monteiro, Ana F. Sequeira, Helder P. Oliveira, Jaime S. Cardoso
Book Chapter Computer Vision, Imaging and Computer Graphics: Theory and Applications (Springer)

bibtex

@inbook{JoaoCMonteiro2014, author="Joao C. Monteiro and Ana F. Sequeira and Helder P. Oliveira and Jaime S. Cardoso", editor= "Sebastiano Battiano and Sabine Coquillart and Robert Laramee and Andreas Kerren and Jose Braz", title = "Computer Vision, Imaging and Computer Graphics: Theory and Applications", chapter= "Robust Iris Localisation in Challenging Scenarios", pages = "146--162", publisher = "Springer", year= "2014", url = "http://www.inescporto.pt/~jsc/publications/conferences/2014JMonteiroCVICG.pdf", }

Current Teaching

  • 2018 2017

    Statistics and Probability

    1st semester, FEUP/DEEC, MIEEC, 2 year, T and P

  • 2018 2017

    Machine Learning

    1st semester, FEUP/DEEC, PDEEC

Teaching History

  • 2017 2016

    Programming 2

    2nd semester, FEUP/DEEC, MIEEC, 1 year, L

  • 2017 2016

    Image Analysis and Recognition

    2nd semester, FEUP/DEEC, PDEEC

  • 2017 2016

    Statistics and Probability

    1st semester, FEUP/DEEC, MIEEC, 2 year, T and P

  • 2017 2016

    Machine Learning

    1st semester, FEUP/DEEC, PDEEC

  • 2016 2015

    Information Theory

    2nd semester, FEUP/DEEC, PDEEC

  • 2016 2015

    Information Theory

    2nd semester, FEUP/DEEC, MEINF

  • 2016 2015

    Computational Learning

    2nd semester, FEUP/DEEC, MEINF

  • 2016 2015

    Statistics and Probability

    1st semester, FEUP/DEEC, MIEEC, 2 year, T and P

  • 2016 2015

    Machine Learning

    1st semester, FEUP/DEEC, PDEEC

  • 2015 2014

    Information Theory

    2nd semester, FEUP/DEEC, PDEEC

  • 2015 2014

    Information Theory

    2nd semester, FEUP/DEEC, MEINF

  • 2015 2014

    Computational Learning

    2nd semester, FEUP/DEEC, MEINF

  • 2015 2014

    Statistics and Probability

    1st semester, FEUP/DEEC, MIEEC, 2 year, T and P

  • 2015 2014

    Machine Learning

    1st semester, FEUP/DEEC, PDEEC

At My Office

You can find me at my office located at University of Porto.

I am at my office every day, but you may consider a call to fix an appointment.

At My Work

You can find me at my Work located at University of Porto.

I am at my office every day, but you may consider a call to fix an appointment.

At My Lab

You can find me at my office located at University of Porto.

I am at my office every day, but you may consider a call to fix an appointment.