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| Author | X. Binefa; Jordi Vitria; Xavier Roca | ||||
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Deteccion de profundidad en imagenes monoculares mediante vision activa. | Type | Miscellaneous | ||
| Year | 1993 | Publication | Revista de Optica Pura y Aplicada, 26,3:636–648. | Abbreviated Journal | |
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| Notes | OR;ISE;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ BVR1993 | Serial | 144 | ||
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| Author | X. Binefa; Jordi Vitria; Xavier Roca | ||||
| Title |
Deteccion de profundidad en imagenes monoculares mediante vision activa. | Type | Miscellaneous | ||
| Year | 1992 | Publication | I Reunion Iberoamericana de Optica | Abbreviated Journal | |
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| Address | Barcelona | ||||
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| Notes | OR;ISE;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ BVR1992 | Serial | 258 | ||
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| Author | Fadi Dornaika; Bogdan Raducanu | ||||
| Title |
Detecting and Tracking of 3D Face Pose for Human-Robot Interaction | Type | Conference Article | ||
| Year | 2008 | Publication | IEEE International Conference on Robotics and Automation, | Abbreviated Journal | |
| Volume | Issue | Pages | 1716–1721 | ||
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| Address | Pasadena; CA; USA | ||||
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| Area | Expedition | Conference | ICRA | ||
| Notes | OR;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ DoR2008a | Serial | 982 | ||
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| Author | Dimosthenis Karatzas | ||||
| Title |
Detecting Gradients in Text Images Using the Hough Transform | Type | Conference Article | ||
| Year | 2008 | Publication | Proceedings of the 8th International Workshop on Document Analysis Systems, | Abbreviated Journal | |
| Volume | Issue | Pages | 245–252 | ||
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| Address | Nara (Japan) | ||||
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| Area | Expedition | Conference | DAS | ||
| Notes | DAG | Approved | no | ||
| Call Number | DAG @ dag @ Kar2008 | Serial | 1062 | ||
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| Author | David Roche; Debora Gil; Jesus Giraldo | ||||
| Title |
Detecting loss of diversity for an efficient termination of EAs | Type | Conference Article | ||
| Year | 2013 | Publication | 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing | Abbreviated Journal | |
| Volume | Issue | Pages | 561 - 566 | ||
| Keywords | EA termination; EA population diversity; EA steady state | ||||
| Abstract | Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence. Experiments show that our condition works regardless of the search space dimension and function landscape. |
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| Address | Timisoara; Rumania; | ||||
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| ISSN | ISBN | 978-1-4799-3035-7 | Medium | ||
| Area | Expedition | Conference | SYNASC | ||
| Notes | IAM; 600.044; 600.060; 605.203 | Approved | no | ||
| Call Number | Admin @ si @ RGG2013c | Serial | 2299 | ||
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| Author | Petia Radeva; A.F. Sole; Antonio Lopez; Joan Serrat | ||||
| Title |
Detecting Nets of Linear Structures in Satellite Images. | Type | Miscellaneous | ||
| Year | 1998 | Publication | Abbreviated Journal | ||
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| Address | Londres | ||||
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number | ADAS @ adas @ RSL1998 | Serial | 25 | ||
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| Author | Petia Radeva; A.F. Sole; Antonio Lopez; Joan Serrat | ||||
| Title |
Detecting Nets of Linear Structures in Satellite Images. | Type | Miscellaneous | ||
| Year | 1999 | Publication | Machine Vision and Advanced Image Processing in Remote Sensing, Springer, 304–316. | Abbreviated Journal | |
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| Notes | ADAS;MILAB | Approved | no | ||
| Call Number | ADAS @ adas @ RSL1999 | Serial | 34 | ||
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| Author | Marina Alberti | ||||
| Title |
Detection and Alignment of Vascular Structures in Intravascular Ultrasound using Pattern Recognition Techniques | Type | Book Whole | ||
| Year | 2013 | Publication | PhD Thesis, Universitat de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | In this thesis, several methods for the automatic analysis of Intravascular Ultrasound
(IVUS) sequences are presented, aimed at assisting physicians in the diagnosis, the assessment of the intervention and the monitoring of the patients with coronary disease. The basis for the developed frameworks are machine learning, pattern recognition and image processing techniques. First, a novel approach for the automatic detection of vascular bifurcations in IVUS is presented. The task is addressed as a binary classi cation problem (identifying bifurcation and non-bifurcation angular sectors in the sequence images). The multiscale stacked sequential learning algorithm is applied, to take into account the spatial and temporal context in IVUS sequences, and the results are re ned using a-priori information about branching dimensions and geometry. The achieved performance is comparable to intra- and inter-observer variability. Then, we propose a novel method for the automatic non-rigid alignment of IVUS sequences of the same patient, acquired at dierent moments (before and after percutaneous coronary intervention, or at baseline and follow-up examinations). The method is based on the description of the morphological content of the vessel, obtained by extracting temporal morphological pro les from the IVUS acquisitions, by means of methods for segmentation, characterization and detection in IVUS. A technique for non-rigid sequence alignment – the Dynamic Time Warping algorithm - is applied to the pro les and adapted to the speci c clinical problem. Two dierent robust strategies are proposed to address the partial overlapping between frames of corresponding sequences, and a regularization term is introduced to compensate for possible errors in the pro le extraction. The bene ts of the proposed strategy are demonstrated by extensive validation on synthetic and in-vivo data. The results show the interest of the proposed non-linear alignment and the clinical value of the method. Finally, a novel automatic approach for the extraction of the luminal border in IVUS images is presented. The method applies the multiscale stacked sequential learning algorithm and extends it to 2-D+T, in a rst classi cation phase (the identi- cation of lumen and non-lumen regions of the images), while an active contour model is used in a second phase, to identify the lumen contour. The method is extended to the longitudinal dimension of the sequences and it is validated on a challenging data-set. |
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| Address | Barcelona | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Simone Balocco;Petia Radeva | |
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| Notes | MILAB | Approved | no | ||
| Call Number | Admin @ si @ Alb2013 | Serial | 2215 | ||
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| Author | Ivan Huerta; Michael Holte; Thomas B. Moeslund; Jordi Gonzalez | ||||
| Title |
Detection and Removal of Chromatic Moving Shadows in Surveillance Scenarios | Type | Conference Article | ||
| Year | 2009 | Publication | 12th International Conference on Computer Vision | Abbreviated Journal | |
| Volume | Issue | Pages | 1499 - 1506 | ||
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| Abstract | Segmentation in the surveillance domain has to deal with shadows to avoid distortions when detecting moving objects. Most segmentation approaches dealing with shadow detection are typically restricted to penumbra shadows. Therefore, such techniques cannot cope well with umbra shadows. Consequently, umbra shadows are usually detected as part of moving objects. In this paper we present a novel technique based on gradient and colour models for separating chromatic moving cast shadows from detected moving objects. Firstly, both a chromatic invariant colour cone model and an invariant gradient model are built to perform automatic segmentation while detecting potential shadows. In a second step, regions corresponding to potential shadows are grouped by considering “a bluish effect” and an edge partitioning. Lastly, (i) temporal similarities between textures and (ii) spatial similarities between chrominance angle and brightness distortions are analysed for all potential shadow regions in order to finally identify umbra shadows. Unlike other approaches, our method does not make any a-priori assumptions about camera location, surface geometries, surface textures, shapes and types of shadows, objects, and background. Experimental results show the performance and accuracy of our approach in different shadowed materials and illumination conditions. | ||||
| Address | Kyoto, Japan | ||||
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| ISSN | 1550-5499 | ISBN | 978-1-4244-4420-5 | Medium | |
| Area | Expedition | Conference | ICCV | ||
| Notes | Approved | no | |||
| Call Number | ISE @ ise @ HHM2009 | Serial | 1213 | ||
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| Author | Sergio Escalera; Oriol Pujol; Petia Radeva | ||||
| Title |
Detection of Complex Salient Regions | Type | Journal | ||
| Year | 2008 | Publication | EURASIP Journal on Advances in Signal Processing, vol. 2008, article ID451389, 11 pages | Abbreviated Journal | |
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| Notes | MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2008b | Serial | 960 | ||
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| Author | Jose Elias Yauri; M. Lagos; H. Vega-Huerta; P. de-la-Cruz; G.L.E Maquen-Niño; E. Condor-Tinoco | ||||
| Title |
Detection of Epileptic Seizures Based-on Channel Fusion and Transformer Network in EEG Recordings | Type | Journal Article | ||
| Year | 2023 | Publication | International Journal of Advanced Computer Science and Applications | Abbreviated Journal | IJACSA |
| Volume | 14 | Issue | 5 | Pages | 1067-1074 |
| Keywords | Epilepsy; epilepsy detection; EEG; EEG channel fusion; convolutional neural network; self-attention | ||||
| Abstract | According to the World Health Organization, epilepsy affects more than 50 million people in the world, and specifically, 80% of them live in developing countries. Therefore, epilepsy has become among the major public issue for many governments and deserves to be engaged. Epilepsy is characterized by uncontrollable seizures in the subject due to a sudden abnormal functionality of the brain. Recurrence of epilepsy attacks change people’s lives and interferes with their daily activities. Although epilepsy has no cure, it could be mitigated with an appropriated diagnosis and medication. Usually, epilepsy diagnosis is based on the analysis of an electroencephalogram (EEG) of the patient. However, the process of searching for seizure patterns in a multichannel EEG recording is a visual demanding and time consuming task, even for experienced neurologists. Despite the recent progress in automatic recognition of epilepsy, the multichannel nature of EEG recordings still challenges current methods. In this work, a new method to detect epilepsy in multichannel EEG recordings is proposed. First, the method uses convolutions to perform channel fusion, and next, a self-attention network extracts temporal features to classify between interictal and ictal epilepsy states. The method was validated in the public CHB-MIT dataset using the k-fold cross-validation and achieved 99.74% of specificity and 99.15% of sensitivity, surpassing current approaches. | ||||
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| Notes | IAM | Approved | no | ||
| Call Number | Admin @ si @ | Serial | 3856 | ||
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| Author | Antonio Lopez; Cristina Cañero; Joan Serrat; J. Saludes; Felipe Lumbreras; T. Graf | ||||
| Title |
Detection of lane markings based on ridgeness and RANSAC | Type | Miscellaneous | ||
| Year | 2005 | Publication | Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 733–738 | Abbreviated Journal | |
| Volume | Issue | Pages | |||
| Keywords | lane markings | ||||
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| Address | Vienna (Austria) | ||||
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| Notes | ADAS | Approved | no | ||
| Call Number | ADAS @ adas @ LCS2005 | Serial | 588 | ||
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| Author | Diana Ramirez Cifuentes; Ana Freire; Ricardo Baeza Yates; Joaquim Punti Vidal; Pilar Medina Bravo; Diego Velazquez; Josep M. Gonfaus; Jordi Gonzalez | ||||
| Title |
Detection of Suicidal Ideation on Social Media: Multimodal, Relational, and Behavioral Analysis | Type | Journal Article | ||
| Year | 2020 | Publication | Journal of Medical Internet Research | Abbreviated Journal | JMIR |
| Volume | 22 | Issue | 7 | Pages | e17758 |
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| Abstract | Background:
Suicide risk assessment usually involves an interaction between doctors and patients. However, a significant number of people with mental disorders receive no treatment for their condition due to the limited access to mental health care facilities; the reduced availability of clinicians; the lack of awareness; and stigma, neglect, and discrimination surrounding mental disorders. In contrast, internet access and social media usage have increased significantly, providing experts and patients with a means of communication that may contribute to the development of methods to detect mental health issues among social media users. Objective: This paper aimed to describe an approach for the suicide risk assessment of Spanish-speaking users on social media. We aimed to explore behavioral, relational, and multimodal data extracted from multiple social platforms and develop machine learning models to detect users at risk. Methods: We characterized users based on their writings, posting patterns, relations with other users, and images posted. We also evaluated statistical and deep learning approaches to handle multimodal data for the detection of users with signs of suicidal ideation (suicidal ideation risk group). Our methods were evaluated over a dataset of 252 users annotated by clinicians. To evaluate the performance of our models, we distinguished 2 control groups: users who make use of suicide-related vocabulary (focused control group) and generic random users (generic control group). Results: We identified significant statistical differences between the textual and behavioral attributes of each of the control groups compared with the suicidal ideation risk group. At a 95% CI, when comparing the suicidal ideation risk group and the focused control group, the number of friends (P=.04) and median tweet length (P=.04) were significantly different. The median number of friends for a focused control user (median 578.5) was higher than that for a user at risk (median 372.0). Similarly, the median tweet length was higher for focused control users, with 16 words against 13 words of suicidal ideation risk users. Our findings also show that the combination of textual, visual, relational, and behavioral data outperforms the accuracy of using each modality separately. We defined text-based baseline models based on bag of words and word embeddings, which were outperformed by our models, obtaining an increase in accuracy of up to 8% when distinguishing users at risk from both types of control users. Conclusions: The types of attributes analyzed are significant for detecting users at risk, and their combination outperforms the results provided by generic, exclusively text-based baseline models. After evaluating the contribution of image-based predictive models, we believe that our results can be improved by enhancing the models based on textual and relational features. These methods can be extended and applied to different use cases related to other mental disorders. |
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| Notes | ISE; 600.098; 600.119 | Approved | no | ||
| Call Number | Admin @ si @ RFB2020 | Serial | 3552 | ||
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| Author | Xavier Otazu; M. Ribo; M. Peracaula; J.M. Paredes; J. Nuñez | ||||
| Title |
Detection of superimposed periodic signals using wavelets | Type | Journal | ||
| Year | 2002 | Publication | Monthly Notices of the Royal Astronomical Society, 333, 2: 365–372 (IF: 4.671) | Abbreviated Journal | |
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| Notes | CIC | Approved | no | ||
| Call Number | CAT @ cat @ ORP2002 | Serial | 272 | ||
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| Author | Santiago Segui; Michal Drozdzal; Ekaterina Zaytseva; Fernando Azpiroz; Petia Radeva; Jordi Vitria | ||||
| Title |
Detection of wrinkle frames in endoluminal videos using betweenness centrality measures for images | Type | Journal Article | ||
| Year | 2014 | Publication | IEEE Transactions on Information Technology in Biomedicine | Abbreviated Journal | TITB |
| Volume | 18 | Issue | 6 | Pages | 1831-1838 |
| Keywords | Wireless Capsule Endoscopy; Small Bowel Motility Dysfunction; Contraction Detection; Structured Prediction; Betweenness Centrality | ||||
| Abstract | Intestinal contractions are one of the most important events to diagnose motility pathologies of the small intestine. When visualized by wireless capsule endoscopy (WCE), the sequence of frames that represents a contraction is characterized by a clear wrinkle structure in the central frames that corresponds to the folding of the intestinal wall. In this paper we present a new method to robustly detect wrinkle frames in full WCE videos by using a new mid-level image descriptor that is based on a centrality measure proposed for graphs. We present an extended validation, carried out in a very large database, that shows that the proposed method achieves state of the art performance for this task. | ||||
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| Notes | OR; MILAB; 600.046;MV | Approved | no | ||
| Call Number | Admin @ si @ SDZ2014 | Serial | 2385 | ||
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