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| Author | Oriol Pujol; Petia Radeva | ||||
| Title | Texture Segmentation by Statistical Deformable Models | Type | Journal | ||
| Year | 2004 | Publication | International Journal of Image and Graphics | Abbreviated Journal | IJIG |
| Volume | 4 | Issue | 3 | Pages | 433-452 |
| Keywords | Texture segmentation, parametric active contours, statistic snakes | ||||
| Abstract | Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. | ||||
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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PuR2004a | Serial | 505 | ||
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| Author | Sergio Escalera; Oriol Pujol; Petia Radeva | ||||
| Title | Boosted Landmarks of Contextual Descriptors and Forest-ECOC: a Novel Framework to Detect and Classify Objects in Cluttered Scenes | Type | Journal | ||
| Year | 2007 | Publication | Abbreviated Journal | ||
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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2007c | Serial | 907 | ||
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| Author | Oriol Pujol; Sergio Escalera; Petia Radeva | ||||
| Title | An Incremental Node Embedding Technique for Error Correcting Output Codes | Type | Journal | ||
| Year | 2008 | Publication | Pattern Recognition | Abbreviated Journal | PR |
| Volume | 41 | Issue | 2 | Pages | 713–725 |
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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PER2008 | Serial | 942 | ||
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| Author | Sergio Escalera; David M.J. Tax; Oriol Pujol; Petia Radeva; Robert P.W. Duin | ||||
| Title | Subclass Problem-Dependent Design for Error-Correcting Output Codes | Type | Journal | ||
| Year | 2008 | Publication | IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.30(6):1041–1054 | Abbreviated Journal | |
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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ ETP2008 | Serial | 951 | ||
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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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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ EPR2008b | Serial | 960 | ||
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| Author | Oriol Rodriguez-Leor; Carlo Gatta; E. Fernandez-Nofrerias; Oriol Pujol; Neus Salvatella; C. Bosch; H. Tizon; Petia Radeva; J. Mauri | ||||
| Title | Computationally Efficient Image-based IVUS Pullbacks Gating | Type | Journal | ||
| Year | 2008 | Publication | European Heart Journal, ESC Supplement, Munich, 2008, p. 775 | Abbreviated Journal | |
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MILAB;HuPBA | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RGF2008 | Serial | 1036 | ||
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| Author | Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; M. Gomez; Antonio Tovar; L. Cano; C. Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva | ||||
| Title | Ecografia Intracoronaria: Segmentacio Automatica de area de la llum | Type | Journal | ||
| Year | 2002 | Publication | Revista Societat Catalana de Cardiologia | Abbreviated Journal | |
| Volume | 4 | Issue | 4 | Pages | 42 |
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| Address | Barcelona | ||||
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| Area | Expedition | Conference | XIVe Congres de la Societat Catalana de Cardiologia | ||
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MILAB;IAM | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RMF2002 | Serial | 435 | ||
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| Author | Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva | ||||
| Title | Utilizacion de la estructura de los campos vectoriales para la deteccion de la Adventicia en imagenes de Ecografia Intracoronaria | Type | Journal | ||
| Year | 2004 | Publication | Revista Española de Cardiología | Abbreviated Journal | REC |
| Volume | 57 | Issue | 2 | Pages | 100 |
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| Area | Expedition | Conference | SEC | ||
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MILAB;IAM | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RMF2004 | Serial | 566 | ||
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| Author | Cristina Cañero; Fernando Vilariño; Petia Radeva | ||||
| Title | Predictive (un) distortion model and 3D Reconstruction by Biplane Snakes | Type | Journal | ||
| Year | 2002 | Publication | IEEE Transactions on Medical Imaging (IF: 2.911) | Abbreviated Journal | |
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MILAB;SIAI | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ CVR2002 | Serial | 269 | ||
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| Author | Patricia Suarez; Henry Velesaca; Dario Carpio; Angel Sappa | ||||
| Title | Corn kernel classification from few training samples | Type | Journal | ||
| Year | 2023 | Publication | Artificial Intelligence in Agriculture | Abbreviated Journal | |
| Volume | 9 | Issue | Pages | 89-99 | |
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| Abstract | This article presents an efficient approach to classify a set of corn kernels in contact, which may contain good, or defective kernels along with impurities. The proposed approach consists of two stages, the first one is a next-generation segmentation network, trained by using a set of synthesized images that is applied to divide the given image into a set of individual instances. An ad-hoc lightweight CNN architecture is then proposed to classify each instance into one of three categories (ie good, defective, and impurities). The segmentation network is trained using a strategy that avoids the time-consuming and human-error-prone task of manual data annotation. Regarding the classification stage, the proposed ad-hoc network is designed with only a few sets of layers to result in a lightweight architecture capable of being used in integrated solutions. Experimental results and comparisons with previous approaches showing both the improvement in accuracy and the reduction in time are provided. Finally, the segmentation and classification approach proposed can be easily adapted for use with other cereal types. | ||||
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MSIAU | Approved | no | ||
| Call Number | Admin @ si @ SVC2023 | Serial | 3892 | ||
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| Author | Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo | ||||
| Title | Detailed 3D face reconstruction from a single RGB image | Type | Journal | ||
| Year | 2019 | Publication | Journal of WSCG | Abbreviated Journal | JWSCG |
| Volume | 27 | Issue | 2 | Pages | 103-112 |
| Keywords | 3D Wrinkle Reconstruction; Face Analysis, Optimization. | ||||
| Abstract | This paper introduces a method to obtain a detailed 3D reconstruction of facial skin from a single RGB image.
To this end, we propose the exclusive use of an input image without requiring any information about the observed material nor training data to model the wrinkle properties. They are detected and characterized directly from the image via a simple and effective parametric model, determining several features such as location, orientation, width, and height. With these ingredients, we propose to minimize a photometric error to retrieve the final detailed 3D map, which is initialized by current techniques based on deep learning. In contrast with other approaches, we only require estimating a depth parameter, making our approach fast and intuitive. Extensive experimental evaluation is presented in a wide variety of synthetic and real images, including different skin properties and facial expressions. In all cases, our method outperforms the current approaches regarding 3D reconstruction accuracy, providing striking results for both large and fine wrinkles. |
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| Address | 2019/11 | ||||
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MSIAU; 600.086; 600.130; 600.122 | Approved | no | ||
| Call Number | Admin @ si @ | Serial | 3708 | ||
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| Author | Patrick Brandao; O. Zisimopoulos; E. Mazomenos; G. Ciutib; Jorge Bernal; M. Visentini-Scarzanell; A. Menciassi; P. Dario; A. Koulaouzidis; A. Arezzo; D.J. Hawkes; D. Stoyanov | ||||
| Title | Towards a computed-aided diagnosis system in colonoscopy: Automatic polyp segmentation using convolution neural networks | Type | Journal | ||
| Year | 2018 | Publication | Journal of Medical Robotics Research | Abbreviated Journal | JMRR |
| Volume | 3 | Issue | 2 | Pages | |
| Keywords | convolutional neural networks; colonoscopy; computer aided diagnosis | ||||
| Abstract | Early diagnosis is essential for the successful treatment of bowel cancers including colorectal cancer (CRC) and capsule endoscopic imaging with robotic actuation can be a valuable diagnostic tool when combined with automated image analysis. We present a deep learning rooted detection and segmentation framework for recognizing lesions in colonoscopy and capsule endoscopy images. We restructure established convolution architectures, such as VGG and ResNets, by converting them into fully-connected convolution networks (FCNs), ne-tune them and study their capabilities for polyp segmentation and detection. We additionally use Shape-from-Shading (SfS) to recover depth and provide a richer representation of the tissue's structure in colonoscopy images. Depth is
incorporated into our network models as an additional input channel to the RGB information and we demonstrate that the resulting network yields improved performance. Our networks are tested on publicly available datasets and the most accurate segmentation model achieved a mean segmentation IU of 47.78% and 56.95% on the ETIS-Larib and CVC-Colon datasets, respectively. For polyp detection, the top performing models we propose surpass the current state of the art with detection recalls superior to 90% for all datasets tested. To our knowledge, we present the rst work to use FCNs for polyp segmentation in addition to proposing a novel combination of SfS and RGB that boosts performance. |
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MV; no menciona | Approved | no | ||
| Call Number | BZM2018 | Serial | 2976 | ||
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| Author | Xim Cerda-Company; Olivier Penacchio; Xavier Otazu | ||||
| Title | Chromatic Induction in Migraine | Type | Journal | ||
| Year | 2021 | Publication | VISION | Abbreviated Journal | |
| Volume | 5 | Issue | 3 | Pages | 37 |
| Keywords | migraine; vision; colour; colour perception; chromatic induction; psychophysics | ||||
| Abstract | The human visual system is not a colorimeter. The perceived colour of a region does not only depend on its colour spectrum, but also on the colour spectra and geometric arrangement of neighbouring regions, a phenomenon called chromatic induction. Chromatic induction is thought to be driven by lateral interactions: the activity of a central neuron is modified by stimuli outside its classical receptive field through excitatory–inhibitory mechanisms. As there is growing evidence of an excitation/inhibition imbalance in migraine, we compared chromatic induction in migraine and control groups. As hypothesised, we found a difference in the strength of induction between the two groups, with stronger induction effects in migraine. On the other hand, given the increased prevalence of visual phenomena in migraine with aura, we also hypothesised that the difference between migraine and control would be more important in migraine with aura than in migraine without aura. Our experiments did not support this hypothesis. Taken together, our results suggest a link between excitation/inhibition imbalance and increased induction effects. | ||||
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NEUROBIT; no proj | Approved | no | ||
| Call Number | Admin @ si @ CPO2021 | Serial | 3589 | ||
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| Author | Oriol Pujol; Petia Radeva; Jordi Vitria | ||||
| Title | Discriminant ECOC: A Heuristic Method for Application Dependent Design of Error Correcting Output Codes | Type | Journal | ||
| Year | 2006 | Publication | IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(6): 1007–1012 | Abbreviated Journal | |
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OR;MILAB;HuPBA;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ PRV2006a | Serial | 646 | ||
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| Author | Petia Radeva; Jordi Vitria | ||||
| Title | Corkinspect: Statistical Learning of Natural Material | Type | Journal | ||
| Year | 2004 | Publication | Italian Beverage Technology, 13(38):11–18 | Abbreviated Journal | |
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OR;MILAB;MV | Approved | no | ||
| Call Number | BCNPCL @ bcnpcl @ RaV2004b | Serial | 514 | ||
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