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Author | Albert Gordo; Florent Perronnin | ||||
Title | A Bag-of-Pages Approach to Unordered Multi-Page Document Classification | Type | Conference Article | ||
Year | 2010 | Publication | 20th International Conference on Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1920–1923 | ||
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Abstract | We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system. | ||||
Address | Istanbul (Turkey) | ||||
Corporate Author | Thesis | ||||
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Series Volume | Series Issue | Edition | |||
ISSN | 1051-4651 | ISBN | 978-1-4244-7542-1 | Medium | |
Area | Expedition | Conference | ICPR | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ GoP2010 | Serial | 1480 | ||
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Author | Anjan Dutta; Josep Llados; Umapada Pal | ||||
Title | A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings | Type | Conference Article | ||
Year | 2011 | Publication | 5th Iberian Conference on Pattern Recognition and Image Analysis | Abbreviated Journal | |
Volume | 6669 | Issue | Pages | 620-627 | |
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Abstract | In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. | ||||
Address | Las Palmas de Gran Canaria. Spain | ||||
Corporate Author | Thesis | ||||
Publisher | Springer Berlin Heidelberg | Place of Publication | Berlin | Editor | Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
Language | Summary Language | Original Title | |||
Series Editor | Series Title | Abbreviated Series Title | LNCS | ||
Series Volume | Series Issue | Edition | |||
ISSN | 0302-9743 | ISBN | 978-3-642-21256-7 | Medium | |
Area | Expedition | Conference | IbPRIA | ||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ DLP2011a | Serial | 1738 | ||
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Author | David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville | ||||
Title | A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images | Type | Conference Article | ||
Year | 2017 | Publication | 31st International Congress and Exhibition on Computer Assisted Radiology and Surgery | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Deep Learning; Medical Imaging | ||||
Abstract | Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss-rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aiming to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. We provide new baselines on this dataset by training standard fully convolutional networks (FCN) for semantic segmentation and significantly outperforming, without any further post-processing, prior results in endoluminal scene segmentation. | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | CARS | ||
Notes | ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 | Approved | no | ||
Call Number | ADAS @ adas @ VBS2017a | Serial | 2880 | ||
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Author | David Vazquez; Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Antonio Lopez; Adriana Romero; Michal Drozdzal; Aaron Courville | ||||
Title | A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images | Type | Journal Article | ||
Year | 2017 | Publication | Journal of Healthcare Engineering | Abbreviated Journal | JHCE |
Volume | Issue | Pages | 2040-2295 | ||
Keywords | Colonoscopy images; Deep Learning; Semantic Segmentation | ||||
Abstract | Colorectal cancer (CRC) is the third cause of cancer death world-wide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for polyps and colonoscopy is the screening tool of choice. The main limitations of this screening procedure are polyp miss- rate and inability to perform visual assessment of polyp malignancy. These drawbacks can be reduced by designing Decision Support Systems (DSS) aim- ing to help clinicians in the different stages of the procedure by providing endoluminal scene segmentation. Thus, in this paper, we introduce an extended benchmark of colonoscopy image segmentation, with the hope of establishing a new strong benchmark for colonoscopy image analysis research. The proposed dataset consists of 4 relevant classes to inspect the endolumninal scene, tar- geting different clinical needs. Together with the dataset and taking advantage of advances in semantic segmentation literature, we provide new baselines by training standard fully convolutional networks (FCN). We perform a compar- ative study to show that FCN significantly outperform, without any further post-processing, prior results in endoluminal scene segmentation, especially with respect to polyp segmentation and localization. | ||||
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Notes | ADAS; MV; 600.075; 600.085; 600.076; 601.281; 600.118 | Approved | no | ||
Call Number | VBS2017b | Serial | 2940 | ||
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Author | Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil | ||||
Title | A benchmark for the evaluation of computational methods for bronchoscopic navigation | Type | Journal Article | ||
Year | 2022 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCARS |
Volume | 17 | Issue | 1 | Pages | |
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Area | Expedition | Conference | |||
Notes | IAM | Approved | no | ||
Call Number | Admin @ si @ BSC2022 | Serial | 3832 | ||
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Author | Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre | ||||
Title | A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts | Type | Conference Article | ||
Year | 2014 | Publication | Digital Access to Textual Cultural Heritage Conference | Abbreviated Journal | |
Volume | Issue | Pages | 103-108 | ||
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Abstract | In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts. | ||||
Address | Madrid; May 2014 | ||||
Corporate Author | Thesis | ||||
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ISSN | ISBN | 978-1-4503-2588-2 | Medium | ||
Area | Expedition | Conference | DATeCH | ||
Notes | DAG; 600.061; 602.006; 600.077 | Approved | no | ||
Call Number | Admin @ si @ FLM2014 | Serial | 2516 | ||
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Author | Shigang Yue; F. Claire Rind; Matthias S. Keil; Jorge Cuadri; Richard Stafford | ||||
Title | A bio-inspired visual collision detection mechanism for cars: Optimisation of a model of a locust neuron to a novel environment | Type | Journal | ||
Year | 2006 | Publication | Neurocomputing 69(13–15): 1591–1598 | Abbreviated Journal | |
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Notes | Approved | no | |||
Call Number | Admin @ si @ YRK2006 | Serial | 652 | ||
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Author | Ali Furkan Biten | ||||
Title | A Bitter-Sweet Symphony on Vision and Language: Bias and World Knowledge | Type | Book Whole | ||
Year | 2022 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
Volume | Issue | Pages | |||
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Abstract | Vision and Language are broadly regarded as cornerstones of intelligence. Even though language and vision have different aims – language having the purpose of communication, transmission of information and vision having the purpose of constructing mental representations around us to navigate and interact with objects – they cooperate and depend on one another in many tasks we perform effortlessly. This reliance is actively being studied in various Computer Vision tasks, e.g. image captioning, visual question answering, image-sentence retrieval, phrase grounding, just to name a few. All of these tasks share the inherent difficulty of the aligning the two modalities, while being robust to language
priors and various biases existing in the datasets. One of the ultimate goal for vision and language research is to be able to inject world knowledge while getting rid of the biases that come with the datasets. In this thesis, we mainly focus on two vision and language tasks, namely Image Captioning and Scene-Text Visual Question Answering (STVQA). In both domains, we start by defining a new task that requires the utilization of world knowledge and in both tasks, we find that the models commonly employed are prone to biases that exist in the data. Concretely, we introduce new tasks and discover several problems that impede performance at each level and provide remedies or possible solutions in each chapter: i) We define a new task to move beyond Image Captioning to Image Interpretation that can utilize Named Entities in the form of world knowledge. ii) We study the object hallucination problem in classic Image Captioning systems and develop an architecture-agnostic solution. iii) We define a sub-task of Visual Question Answering that requires reading the text in the image (STVQA), where we highlight the limitations of current models. iv) We propose an architecture for the STVQA task that can point to the answer in the image and show how to combine it with classic VQA models. v) We show how far language can get us in STVQA and discover yet another bias which causes the models to disregard the image while doing Visual Question Answering. |
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Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | IMPRIMA | Place of Publication | Editor | Dimosthenis Karatzas;Lluis Gomez | |
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-84-124793-5-5 | Medium | ||
Area | Expedition | Conference | |||
Notes | DAG | Approved | no | ||
Call Number | Admin @ si @ Bit2022 | Serial | 3755 | ||
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Author | Isabelle Guyon; Imad Chaabane; Hugo Jair Escalante; Sergio Escalera; Damir Jajetic; James Robert Lloyd; Nuria Macia; Bisakha Ray; Lukasz Romaszko; Michele Sebag; Alexander Statnikov; Sebastien Treguer; Evelyne Viegas | ||||
Title | A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention | Type | Conference Article | ||
Year | 2016 | Publication | AutoML Workshop | Abbreviated Journal | |
Volume | Issue | 1 | Pages | 1-8 | |
Keywords | AutoML Challenge; machine learning; model selection; meta-learning; repre- sentation learning; active learning | ||||
Abstract | The ChaLearn AutoML Challenge team conducted a large scale evaluation of fully automatic, black-box learning machines for feature-based classification and regression problems. The test bed was composed of 30 data sets from a wide variety of application domains and ranged across different types of complexity. Over six rounds, participants succeeded in delivering AutoML software capable of being trained and tested without human intervention. Although improvements can still be made to close the gap between human-tweaked and AutoML models, this competition contributes to the development of fully automated environments by challenging practitioners to solve problems under specific constraints and sharing their approaches; the platform will remain available for post-challenge submissions at http://codalab.org/AutoML. | ||||
Address | New York; USA; June 2016 | ||||
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Area | Expedition | Conference | ICML | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GCE2016 | Serial | 2769 | ||
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Author | Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti | ||||
Title | A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa | Type | Conference Article | ||
Year | 2003 | Publication | Proceedings of Pattern Recognition in Information Systems | Abbreviated Journal | |
Volume | Issue | Pages | 1-13 | ||
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Address | Angers, France | ||||
Corporate Author | Thesis | ||||
Publisher | ICEIS Press | Place of Publication | Editor | ||
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ISSN | ISBN | 972-98816-3-4 | Medium | ||
Area | Expedition | Conference | PRIS'03 | ||
Notes | DAG;IAM; | Approved | no | ||
Call Number | IAM @ iam @ LVS2003 | Serial | 1576 | ||
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Author | Onur Ferhat; Fernando Vilariño | ||||
Title | A Cheap Portable Eye-Tracker Solution for Common Setups | Type | Conference Article | ||
Year | 2013 | Publication | 17th European Conference on Eye Movements | Abbreviated Journal | |
Volume | Issue | Pages | |||
Keywords | Low cost; eye-tracker; software; webcam; Raspberry Pi | ||||
Abstract | We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system. After assessing the accuracy of our eye-tracker in elaborated experiments involving 18 subjects under 4 different system setups, we developed a simple game to see how it performs in practice and we also installed it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.62° horizontal accuracy with 3 fps refresh rate for a building cost of 70 Euros. | ||||
Address | Lund; Sweden; August 2013 | ||||
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Area | Expedition | Conference | ECEM | ||
Notes | MV;SIAI | Approved | no | ||
Call Number | Admin @ si @ FeV2013 | Serial | 2374 | ||
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Author | Onur Ferhat; Fernando Vilariño; F. Javier Sanchez | ||||
Title | A cheap portable eye-tracker solution for common setups. | Type | Journal Article | ||
Year | 2014 | Publication | Journal of Eye Movement Research | Abbreviated Journal | JEMR |
Volume | 7 | Issue | 3 | Pages | 1-10 |
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Abstract | We analyze the feasibility of a cheap eye-tracker where the hardware consists of a single webcam and a Raspberry Pi device. Our aim is to discover the limits of such a system and to see whether it provides an acceptable performance. We base our work on the open source Opengazer (Zielinski, 2013) and we propose several improvements to create a robust, real-time system which can work on a computer with 30Hz sampling rate. After assessing the accuracy of our eye-tracker in elaborated experiments involving 12 subjects under 4 different system setups, we install it on a Raspberry Pi to create a portable stand-alone eye-tracker which achieves 1.42° horizontal accuracy with 3Hz refresh rate for a building cost of 70 Euros. | ||||
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Notes | ;SIAI | Approved | no | ||
Call Number | Admin @ si @ FVS2014 | Serial | 2435 | ||
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Author | Lubomir Latchev; Maya Dimitrova; David Rotger | ||||
Title | A Classifier of Technical Diagnostic States of Electrocardiograph | Type | Miscellaneous | ||
Year | 2006 | Publication | International Conference on Computer Systems and Technologies (CompSysTech´06), 15.1–15.6 | Abbreviated Journal | |
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Address | University of Veliko Tarnovo (Bulgaria) | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ LDR2006 | Serial | 774 | ||
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Author | Diego Velazquez; Pau Rodriguez; Josep M. Gonfaus; Xavier Roca; Jordi Gonzalez | ||||
Title | A Closer Look at Embedding Propagation for Manifold Smoothing | Type | Journal Article | ||
Year | 2022 | Publication | Journal of Machine Learning Research | Abbreviated Journal | JMLR |
Volume | 23 | Issue | 252 | Pages | 1-27 |
Keywords | Regularization; emi-supervised learning; self-supervised learning; adversarial robustness; few-shot classification | ||||
Abstract | Supervised training of neural networks requires a large amount of manually annotated data and the resulting networks tend to be sensitive to out-of-distribution (OOD) data.
Self- and semi-supervised training schemes reduce the amount of annotated data required during the training process. However, OOD generalization remains a major challenge for most methods. Strategies that promote smoother decision boundaries play an important role in out-of-distribution generalization. For example, embedding propagation (EP) for manifold smoothing has recently shown to considerably improve the OOD performance for few-shot classification. EP achieves smoother class manifolds by building a graph from sample embeddings and propagating information through the nodes in an unsupervised manner. In this work, we extend the original EP paper providing additional evidence and experiments showing that it attains smoother class embedding manifolds and improves results in settings beyond few-shot classification. Concretely, we show that EP improves the robustness of neural networks against multiple adversarial attacks as well as semi- and self-supervised learning performance. |
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Address | 9/2022 | ||||
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Notes | Approved | no | |||
Call Number | Admin @ si @ VRG2022 | Serial | 3762 | ||
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Author | Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez | ||||
Title | A Coarse-to-fine Approach for fast Deformable Object Detection | Type | Conference Article | ||
Year | 2011 | Publication | IEEE conference on Computer Vision and Pattern Recognition | Abbreviated Journal | |
Volume | Issue | Pages | 1353-1360 | ||
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Address | Colorado Springs; USA | ||||
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Area | Expedition | Conference | CVPR | ||
Notes | ISE | Approved | no | ||
Call Number | Admin @ si @ PVG2011 | Serial | 1764 | ||
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