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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Ana Garcia Rodriguez; Jorge Bernal; F. Javier Sanchez; Henry Cordova; Rodrigo Garces Duran; Cristina Rodriguez de Miguel; Gloria Fernandez Esparrach |
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Title |
Polyp fingerprint: automatic recognition of colorectal polyps’ unique features |
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Journal Article |
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2020 |
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Surgical Endoscopy and other Interventional Techniques |
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SEND |
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34 |
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4 |
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1887-1889 |
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BACKGROUND:
Content-based image retrieval (CBIR) is an application of machine learning used to retrieve images by similarity on the basis of features. Our objective was to develop a CBIR system that could identify images containing the same polyp ('polyp fingerprint').
METHODS:
A machine learning technique called Bag of Words was used to describe each endoscopic image containing a polyp in a unique way. The system was tested with 243 white light images belonging to 99 different polyps (for each polyp there were at least two images representing it in two different temporal moments). Images were acquired in routine colonoscopies at Hospital Clínic using high-definition Olympus endoscopes. The method provided for each image the closest match within the dataset.
RESULTS:
The system matched another image of the same polyp in 221/243 cases (91%). No differences were observed in the number of correct matches according to Paris classification (protruded: 90.7% vs. non-protruded: 91.3%) and size (< 10 mm: 91.6% vs. > 10 mm: 90%).
CONCLUSIONS:
A CBIR system can match accurately two images containing the same polyp, which could be a helpful aid for polyp image recognition.
KEYWORDS:
Artificial intelligence; Colorectal polyps; Content-based image retrieval |
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MV; no menciona |
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Admin @ si @ |
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3403 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Agata Lapedriza; Santiago Segui; David Masip; Jordi Vitria |
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Title |
A Sparse Bayesian Approach for Joint Feature Selection and Classifier Learning |
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2008 |
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Pattern Analysis and Applications, Special Issue: Non–Parametric Distance–Based Classification Techniques and Their Applications, |
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11 |
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3-4 |
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299-308 |
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BCNPCL @ bcnpcl @ LSM2008 |
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996 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
Agata Lapedriza; David Masip; Jordi Vitria |
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Title |
On the Use of External Face Features for Identity Verification |
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2006 |
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Journal of Multimedia, 1(4): 11–20 |
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1 |
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4 |
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11-20 |
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Face Verification, Computer Vision, Machine Learning |
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In general automatic face classification applications images are captured in natural environments. In these cases, the performance is affected by variations in facial images related to illumination, pose, occlusion or expressions. Most of the existing face classification systems use only the internal features information, composed by eyes, nose and mouth, since they are more difficult to imitate. Nevertheless, nowadays a lot of applications not related to security are developed, and in these cases the information located at head, chin or ears zones (external features) can be useful to improve the current accuracies. However, the lack of a natural alignment in these areas makes difficult to extract these features applying classic Bottom-Up methods. In this paper, we propose a complete scheme based on a Top-Down reconstruction algorithm to extract external features of face images. To test our system we have performed face verification experiments using public databases, given that identity verification is a general task that has many real life applications. We have considered images uniformly illuminated, images with occlusions and images with high local changes in the illumination, and the obtained results show that the information contributed by the external features can be useful for verification purposes, specially significant when faces are partially occluded. |
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BCNPCL @ bcnpcl @ LMV2006b |
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708 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A. Pujol; Jordi Vitria; Felipe Lumbreras; Juan J. Villanueva |
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Title |
Topological principal component analysis for face encoding and recognition |
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2001 |
Publication |
Pattern Recognition Letters |
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PRL |
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22 |
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6-7 |
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769–776 |
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IF: 0.552 |
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ADAS @ adas @ PVL2001 |
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155 |
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Author ![sorted by Author field, descending order (down)](http://refbase.cvc.uab.es/img/sort_desc.gif) |
A. Martinez; Jordi Vitria |
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Designing and Implementing Real Walking Agents using Virtual Environments. |
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1995 |
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Madeira, Portugal |
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BCNPCL @ bcnpcl @ MaV1995a |
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121 |
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