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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Touching Text Character Localization in Graphical Documents using SIFT |
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Conference Article |
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2009 |
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In proceedings 8th IAPR International Workshop on Graphics Recognition |
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Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult.
Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. |
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La rochelle; July 2009 |
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GREC |
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DAG |
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DAG @ dag @ RPL2009c |
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1445 |
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Author |
Carlo Gatta; Simone Balocco; Francesco Ciompi; R. Hemetsberger; Oriol Rodriguez-Leor; Petia Radeva |
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Real-time gating of IVUS sequences based on motion blur analysis: Method and quantitative validation |
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Conference Article |
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2010 |
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13th international conference on Medical image computing and computer-assisted intervention |
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II |
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59-67 |
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Intravascular Ultrasound (IVUS) is an image-guiding technique for cardiovascular diagnostic, providing cross-sectional images of vessels. During the acquisition, the catheter is pulled back (pullback) at a constant speed in order to acquire spatially subsequent images of the artery. However, during this procedure, the heart twist produces a swinging fluctuation of the probe position along the vessel axis. In this paper we propose a real-time gating algorithm based on the analysis of motion blur variations during the IVUS sequence. Quantitative tests performed on an in-vitro ground truth data base shown that our method is superior to state of the art algorithms both in computational speed and accuracy. |
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Springer-Verlag Berlin |
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MICCAI |
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MILAB |
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BCNPCL @ bcnpcl @ GBC2010 |
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1447 |
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Author |
Xavier Otazu; C. Alejandro Parraga; Maria Vanrell |
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Title |
Towards a unified chromatic inducction model |
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Journal Article |
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2010 |
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Journal of Vision |
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VSS |
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10 |
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12:5 |
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1-24 |
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Visual system; Color induction; Wavelet transform |
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In a previous work (X. Otazu, M. Vanrell, & C. A. Párraga, 2008b), we showed how several brightness induction effects can be predicted using a simple multiresolution wavelet model (BIWaM). Here we present a new model for chromatic induction processes (termed Chromatic Induction Wavelet Model or CIWaM), which is also implemented on a multiresolution framework and based on similar assumptions related to the spatial frequency and the contrast surround energy of the stimulus. The CIWaM can be interpreted as a very simple extension of the BIWaM to the chromatic channels, which in our case are defined in the MacLeod-Boynton (lsY) color space. This new model allows us to unify both chromatic assimilation and chromatic contrast effects in a single mathematical formulation. The predictions of the CIWaM were tested by means of several color and brightness induction experiments, which showed an acceptable agreement between model predictions and psychophysical data. |
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CIC |
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CAT @ cat @ OPV2010 |
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1450 |
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Author |
Jose Manuel Alvarez; Theo Gevers; Antonio Lopez |
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Title |
Learning photometric invariance for object detection |
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Journal Article |
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Year |
2010 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
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Volume |
90 |
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1 |
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45-61 |
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road detection |
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Impact factor: 3.508 (the last available from JCR2009SCI). Position 4/103 in the category Computer Science, Artificial Intelligence. Quartile
Color is a powerful visual cue in many computer vision applications such as image segmentation and object recognition. However, most of the existing color models depend on the imaging conditions that negatively affect the performance of the task at hand. Often, a reflection model (e.g., Lambertian or dichromatic reflectance) is used to derive color invariant models. However, this approach may be too restricted to model real-world scenes in which different reflectance mechanisms can hold simultaneously.
Therefore, in this paper, we aim to derive color invariance by learning from color models to obtain diversified color invariant ensembles. First, a photometrical orthogonal and non-redundant color model set is computed composed of both color variants and invariants. Then, the proposed method combines these color models to arrive at a diversified color ensemble yielding a proper balance between invariance (repeatability) and discriminative power (distinctiveness). To achieve this, our fusion method uses a multi-view approach to minimize the estimation error. In this way, the proposed method is robust to data uncertainty and produces properly diversified color invariant ensembles. Further, the proposed method is extended to deal with temporal data by predicting the evolution of observations over time.
Experiments are conducted on three different image datasets to validate the proposed method. Both the theoretical and experimental results show that the method is robust against severe variations in imaging conditions. The method is not restricted to a certain reflection model or parameter tuning, and outperforms state-of-the-art detection techniques in the field of object, skin and road recognition. Considering sequential data, the proposed method (extended to deal with future observations) outperforms the other methods |
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Springer US |
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0920-5691 |
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ADAS;ISE |
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ADAS @ adas @ AGL2010c |
Serial |
1451 |
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Author |
Francesco Ciompi; Oriol Pujol; E Fernandez-Nofrerias; J. Mauri; Petia Radeva |
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Title |
Conditional Random Fields for image segmentation in Intravascular Ultrasound |
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Conference Article |
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Year |
2010 |
Publication |
Medical Image Computing in Catalunya: Graduate Student Workshop |
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13–14 |
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We present a Conditional Random Fields based approach for segmenting Intravascular Ultrasond (IVUS) images. The presented method uses a contextual discriminative graphical model to deal with the presence of distorsions and artifacts in IVUS images, that turns the segmentation of interesting regions into a difficult task. An accurate lumen segmentation on IVUS longitudinal images is achieved. |
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Girona |
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MICCAT |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ CPF2010 |
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1453 |
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Author |
Jose Manuel Alvarez; Antonio Lopez |
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Title |
Road Detection Based on Illuminant Invariance |
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Journal Article |
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Year |
2011 |
Publication |
IEEE Transactions on Intelligent Transportation Systems |
Abbreviated Journal |
TITS |
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12 |
Issue |
1 |
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184-193 |
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road detection |
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By using an onboard camera, it is possible to detect the free road surface ahead of the ego-vehicle. Road detection is of high relevance for autonomous driving, road departure warning, and supporting driver-assistance systems such as vehicle and pedestrian detection. The key for vision-based road detection is the ability to classify image pixels as belonging or not to the road surface. Identifying road pixels is a major challenge due to the intraclass variability caused by lighting conditions. A particularly difficult scenario appears when the road surface has both shadowed and nonshadowed areas. Accordingly, we propose a novel approach to vision-based road detection that is robust to shadows. The novelty of our approach relies on using a shadow-invariant feature space combined with a model-based classifier. The model is built online to improve the adaptability of the algorithm to the current lighting and the presence of other vehicles in the scene. The proposed algorithm works in still images and does not depend on either road shape or temporal restrictions. Quantitative and qualitative experiments on real-world road sequences with heavy traffic and shadows show that the method is robust to shadows and lighting variations. Moreover, the proposed method provides the highest performance when compared with hue-saturation-intensity (HSI)-based algorithms. |
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ADAS |
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ADAS @ adas @ AlL2011 |
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1456 |
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Author |
Muhammad Muzzamil Luqman; Josep Llados; Jean-Yves Ramel; Thierry Brouard |
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Title |
A Fuzzy-Interval Based Approach For Explicit Graph Embedding, Recognizing Patterns in Signals, Speech, Images and Video |
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Conference Article |
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Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
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6388 |
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93–98 |
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We present a new method for explicit graph embedding. Our algorithm extracts a feature vector for an undirected attributed graph. The proposed feature vector encodes details about the number of nodes, number of edges, node degrees, the attributes of nodes and the attributes of edges in the graph. The first two features are for the number of nodes and the number of edges. These are followed by w features for node degrees, m features for k node attributes and n features for l edge attributes — which represent the distribution of node degrees, node attribute values and edge attribute values, and are obtained by defining (in an unsupervised fashion), fuzzy-intervals over the list of node degrees, node attributes and edge attributes. Experimental results are provided for sample data of ICPR2010 contest GEPR. |
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Springer, Heidelberg |
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0302-9743 |
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978-3-642-17710-1 |
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ICPR |
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DAG |
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DAG @ dag @ LLR2010 |
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1459 |
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Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados |
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Title |
A Content Spotting System For Line Drawing Graphic Document Images |
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Conference Article |
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2010 |
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20th International Conference on Pattern Recognition |
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20 |
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3420–3423 |
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We present a content spotting system for line drawing graphic document images. The proposed system is sufficiently domain independent and takes the keyword based information retrieval for graphic documents, one step forward, to Query By Example (QBE) and focused retrieval. During offline learning mode: we vectorize the documents in the repository, represent them by attributed relational graphs, extract regions of interest (ROIs) from them, convert each ROI to a fuzzy structural signature, cluster similar signatures to form ROI classes and build an index for the repository. During online querying mode: a Bayesian network classifier recognizes the ROIs in the query image and the corresponding documents are fetched by looking up in the repository index. Experimental results are presented for synthetic images of architectural and electronic documents. |
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1051-4651 |
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978-1-4244-7542-1 |
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ICPR |
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DAG @ dag @ LBR2010b |
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1460 |
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Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
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Title |
Graph of Words Embedding for Molecular Structure-Activity Relationship Analysis |
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Conference Article |
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2010 |
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15th Iberoamerican Congress on Pattern Recognition |
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6419 |
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30–37 |
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Structure-Activity relationship analysis aims at discovering chemical activity of molecular compounds based on their structure. In this article we make use of a particular graph representation of molecules and propose a new graph embedding procedure to solve the problem of structure-activity relationship analysis. The embedding is essentially an arrangement of a molecule in the form of a vector by considering frequencies of appearing atoms and frequencies of covalent bonds between them. Results on two benchmark databases show the effectiveness of the proposed technique in terms of recognition accuracy while avoiding high operational costs in the transformation. |
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Sao Paulo, Brazil |
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0302-9743 |
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978-3-642-16686-0 |
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CIARP |
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DAG @ dag @ GVB2010 |
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1462 |
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Ariel Amato; Mikhail Mozerov; Xavier Roca; Jordi Gonzalez |
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Robust Real-Time Background Subtraction Based on Local Neighborhood Patterns |
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Journal Article |
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2010 |
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EURASIP Journal on Advances in Signal Processing |
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EURASIPJ |
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7 |
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Article ID 901205
This paper describes an efficient background subtraction technique for detecting moving objects. The proposed approach is able to overcome difficulties like illumination changes and moving shadows. Our method introduces two discriminative features based on angular and modular patterns, which are formed by similarity measurement between two sets of RGB color vectors: one belonging to the background image and the other to the current image. We show how these patterns are used to improve foreground detection in the presence of moving shadows and in the case when there are strong similarities in color between background and foreground pixels. Experimental results over a collection of public and own datasets of real image sequences demonstrate that the proposed technique achieves a superior performance compared with state-of-the-art methods. Furthermore, both the low computational and space complexities make the presented algorithm feasible for real-time applications. |
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1110-8657 |
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ISE @ ise @ AMR2010 |
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1463 |
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Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Embedding Random Projections in Regularized Gradient Boosting Machines |
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Conference Article |
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2010 |
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Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases |
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44–53 |
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Barcelona (Spain) |
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SUEMA |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ CPR2010c |
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1466 |
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Pierluigi Casale; Oriol Pujol; Petia Radeva |
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Title |
Classyfing Agitation in Sedated ICU Patients |
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Conference Article |
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2010 |
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Medical Image Computing in Catalunya: Graduate Student Workshop |
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19–20 |
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Agitation is a serious problem in sedated intensive care unit (ICU) patients. In this work, standard machine learning techniques working on wearable accelerometer data have been used to classifying agitation levels achieving very good classification performances. |
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Girona |
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MICCAT |
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MILAB;HUPBA |
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BCNPCL @ bcnpcl @ COR2010 |
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1467 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions |
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Conference Article |
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2010 |
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28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica |
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One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. |
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Madrid (Spain) |
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Area |
800 |
Expedition |
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Conference |
CASEIB |
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Notes |
MV;SIAI |
Approved |
no |
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| |
Call Number |
Admin @ si @ BSV2010 |
Serial |
1469 |
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| Permanent link to this record |
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Author |
Angel Sappa; M.A. Garcia |
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Title |
Aprendiendo a recrear la realidad en 3D |
Type |
Journal |
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Year |
2007 |
Publication |
UAB Divulga, Revista de Divulgacion Cientifica |
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Notes |
spreading |
Approved |
no |
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| |
Call Number |
ADAS @ adas @ SaG2007c |
Serial |
1470 |
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| Permanent link to this record |
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Author |
Joan Serrat; Ferran Diego; Felipe Lumbreras |
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| |
Title |
Los faros delanteros a traves del objetivo |
Type |
Journal |
| |
Year |
2008 |
Publication |
UAB Divulga, Revista de divulgacion cientifica |
Abbreviated Journal |
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Volume |
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Place of Publication |
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Summary Language |
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Area |
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Expedition |
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Conference |
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Notes |
ADAS |
Approved |
no |
|
| |
Call Number |
ADAS @ adas @ SDL2008b |
Serial |
1471 |
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| Permanent link to this record |
