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Author  |
David Masip; Agata Lapedriza; Jordi Vitria |
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Title |
Boosted Online Learning for Face Recognition |
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Journal Article |
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2009 |
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IEEE Transactions on Systems, Man and Cybernetics part B |
Abbreviated Journal |
TSMCB |
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39 |
Issue |
2 |
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530–538 |
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Abstract |
Face recognition applications commonly suffer from three main drawbacks: a reduced training set, information lying in high-dimensional subspaces, and the need to incorporate new people to recognize. In the recent literature, the extension of a face classifier in order to include new people in the model has been solved using online feature extraction techniques. The most successful approaches of those are the extensions of the principal component analysis or the linear discriminant analysis. In the current paper, a new online boosting algorithm is introduced: a face recognition method that extends a boosting-based classifier by adding new classes while avoiding the need of retraining the classifier each time a new person joins the system. The classifier is learned using the multitask learning principle where multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the structure learned previously, being the addition of new classes not computationally demanding. The present proposal has been (experimentally) validated with two different facial data sets by comparing our approach with the current state-of-the-art techniques. The results show that the proposed online boosting algorithm fares better in terms of final accuracy. In addition, the global performance does not decrease drastically even when the number of classes of the base problem is multiplied by eight. |
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1083–4419 |
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BCNPCL @ bcnpcl @ MLV2009 |
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1155 |
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Author |
David Guillamet; Jordi Vitria; B. Shiele |
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Title |
Introducing a weighted non-negative matrix factorization for image classification |
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Journal Article |
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Year |
2003 |
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Pattern Recognition Letters |
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PRL |
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24 |
Issue |
14 |
Pages |
2447–2454 |
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Abstract |
IF: 0.809 |
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BCNPCL @ bcnpcl @ GVS2003 |
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382 |
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Author |
David Guillamet; Jordi Vitria |
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Title |
Evaluation of distance metrics for recognition based on non-negative matrix factorization |
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Journal Article |
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Year |
2003 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
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24 |
Issue |
9-10 |
Pages |
1599 –1605 |
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IF: 0.809 |
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BCNPCL @ bcnpcl @ GuV2003b |
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380 |
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Author |
D. Seron; F. Moreso; C. Gratin; Jordi Vitria; E. Condom |
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Automated classification of renal interstitium and tubules by local texture analysis and a neural network |
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1996 |
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Analytical and Quantitative Cytology and Histology |
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18 |
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5 |
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410-9, PMID: 8908314 |
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OR;MV |
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BCNPCL @ bcnpcl @ SMG1996 |
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76 |
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Author |
Cristina Sanchez Montes; Jorge Bernal; Ana Garcia Rodriguez; Henry Cordova; Gloria Fernandez Esparrach |
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Title |
Revisión de métodos computacionales de detección y clasificación de pólipos en imagen de colonoscopia |
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Journal Article |
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Year |
2020 |
Publication |
Gastroenterología y Hepatología |
Abbreviated Journal |
GH |
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43 |
Issue |
4 |
Pages |
222-232 |
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Computer-aided diagnosis (CAD) is a tool with great potential to help endoscopists in the tasks of detecting and histologically classifying colorectal polyps. In recent years, different technologies have been described and their potential utility has been increasingly evidenced, which has generated great expectations among scientific societies. However, most of these works are retrospective and use images of different quality and characteristics which are analysed off line. This review aims to familiarise gastroenterologists with computational methods and the particularities of endoscopic imaging, which have an impact on image processing analysis. Finally, the publicly available image databases, needed to compare and confirm the results obtained with different methods, are presented. |
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MV; |
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Admin @ si @ SBG2020 |
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3404 |
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