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Author |
C. Alejandro Parraga |
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Title |
Perceptual Psychophysics |
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Book Chapter |
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2015 |
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Biologically-Inspired Computer Vision: Fundamentals and Applications |
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G.Cristobal; M.Keil; L.Perrinet |
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978-3-527-41264-8 |
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CIC; 600.074 |
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Admin @ si @ Par2015 |
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2600 |
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Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters |
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Title |
Fractional Programming Weighted Decoding for Error-Correcting Output Codes |
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Conference Article |
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2015 |
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Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 |
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38-50 |
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In order to increase the classification performance obtained using Error-Correcting Output Codes designs (ECOC), introducing weights in the decoding phase of the ECOC has attracted a lot of interest. In this work, we present a method for ECOC designs that focuses on increasing hypothesis margin on the data samples given a base classifier. While achieving this, we implicitly reward the base classifiers with high performance, whereas punish those with low performance. The resulting objective function is of the fractional programming type and we deal with this problem through the Dinkelbach’s Algorithm. The conducted tests over well known UCI datasets show that the presented method is superior to the unweighted decoding and that it outperforms the results of the state-of-the-art weighted decoding methods in most of the performed experiments. |
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Gunzburg; Germany; June 2015 |
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Springer International Publishing |
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978-3-319-20247-1 |
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MCS |
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HuPBA;MILAB |
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no |
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Admin @ si @ ISS2015 |
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2601 |
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Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro |
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Title |
Improving Bag of Visual Words Representations with Genetic Programming |
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Conference Article |
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2015 |
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IEEE International Joint Conference on Neural Networks IJCNN2015 |
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The bag of visual words is a well established representation in diverse computer vision problems. Taking inspiration from the fields of text mining and retrieval, this representation has proved to be very effective in a large number of domains.
In most cases, a standard term-frequency weighting scheme is considered for representing images and videos in computer vision. This is somewhat surprising, as there are many alternative ways of generating bag of words representations within the text processing community. This paper explores the use of alternative weighting schemes for landmark tasks in computer vision: image
categorization and gesture recognition. We study the suitability of using well-known supervised and unsupervised weighting schemes for such tasks. More importantly, we devise a genetic program that learns new ways of representing images and videos under the bag of visual words representation. The proposed method learns to combine term-weighting primitives trying to maximize the classification performance. Experimental results are reported in standard image and video data sets showing the effectiveness of the proposed evolutionary algorithm. |
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Killarney; Ireland; July 2015 |
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IJCNN |
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HuPBA;MV |
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Admin @ si @ EME2015 |
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2603 |
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Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Alexander Statnikov; Evelyne Viegas |
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Title |
Design of the 2015 ChaLearn AutoML Challenge |
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Conference Article |
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Year |
2015 |
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IEEE International Joint Conference on Neural Networks IJCNN2015 |
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ChaLearn is organizing for IJCNN 2015 an Automatic Machine Learning challenge (AutoML) to solve classification and regression problems from given feature representations, without any human intervention. This is a challenge with code
submission: the code submitted can be executed automatically on the challenge servers to train and test learning machines on new datasets. However, there is no obligation to submit code. Half of the prizes can be won by just submitting prediction results.
There are six rounds (Prep, Novice, Intermediate, Advanced, Expert, and Master) in which datasets of progressive difficulty are introduced (5 per round). There is no requirement to participate in previous rounds to enter a new round. The rounds alternate AutoML phases in which submitted code is “blind tested” on
datasets the participants have never seen before, and Tweakathon phases giving time (' 1 month) to the participants to improve their methods by tweaking their code on those datasets. This challenge will push the state-of-the-art in fully automatic machine learning on a wide range of problems taken from real world
applications. The platform will remain available beyond the termination of the challenge: http://codalab.org/AutoML |
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Killarney; Ireland; July 2015 |
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IJCNN |
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HuPBA;MILAB |
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Admin @ si @ GBC2015a |
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2604 |
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Author |
Frederic Sampedro; Sergio Escalera; Anna Domenech; Ignasi Carrio |
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Title |
A computational framework for cancer response assessment based on oncological PET-CT scans |
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Journal Article |
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2014 |
Publication |
Computers in Biology and Medicine |
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CBM |
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55 |
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92–99 |
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Computer aided diagnosis; Nuclear medicine; Machine learning; Image processing; Quantitative analysis |
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In this work we present a comprehensive computational framework to help in the clinical assessment of cancer response from a pair of time consecutive oncological PET-CT scans. In this scenario, the design and implementation of a supervised machine learning system to predict and quantify cancer progression or response conditions by introducing a novel feature set that models the underlying clinical context is described. Performance results in 100 clinical cases (corresponding to 200 whole body PET-CT scans) in comparing expert-based visual analysis and classifier decision making show up to 70% accuracy within a completely automatic pipeline and 90% accuracy when providing the system with expert-guided PET tumor segmentation masks. |
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HuPBA;MILAB |
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Admin @ si @ SED2014 |
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2606 |
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Author |
Maedeh Aghaei; Petia Radeva |
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Title |
Bag-of-Tracklets for Person Tracking in Life-Logging Data |
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Conference Article |
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Year |
2014 |
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17th International Conference of the Catalan Association for Artificial Intelligence |
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269 |
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35-44 |
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By increasing popularity of wearable cameras, life-logging data analysis is becoming more and more important and useful to derive significant events out of this substantial collection of images. In this study, we introduce a new tracking method applied to visual life-logging, called bag-of-tracklets, which is based on detecting, localizing and tracking of people. Given the low spatial and temporal resolution of the image data, our model generates and groups tracklets in a unsupervised framework and extracts image sequences of person appearance according to a similarity score of the bag-of-tracklets. The model output is a meaningful sequence of events expressing human appearance and tracking them in life-logging data. The achieved results prove the robustness of our model in terms of efficiency and accuracy despite the low spatial and temporal resolution of the data. |
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978-1-61499-451-0 |
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CCIA |
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MILAB |
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Admin @ si @ AgR2015 |
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2607 |
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Author |
Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño |
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Title |
WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians |
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Journal Article |
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2015 |
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Computerized Medical Imaging and Graphics |
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CMIG |
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43 |
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99-111 |
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Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection |
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We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice. |
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0895-6111 |
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MV; IAM; 600.047; 600.060; 600.075;SIAI |
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Admin @ si @ BSF2015 |
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2609 |
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Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell |
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Title |
Quasi-real time digital assessment of Central Airway Obstruction |
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Conference Article |
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2015 |
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3rd European congress for bronchology and interventional pulmonology ECBIP2015 |
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Barcelona; Spain; April 2015 |
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ECBIP |
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IAM; MV; 600.075 |
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SGT2015 |
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2612 |
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Antoni Gurgui; Debora Gil; Enric Marti |
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Title |
Laplacian Unitary Domain for Texture Morphing |
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Conference Article |
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2015 |
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Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 |
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1 |
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693-699 |
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Facial; metamorphosis;LaplacianMorphing |
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Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them. |
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Munich; Germany; February 2015 |
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SciTePress |
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978-989-758-089-5 |
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VISAPP |
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IAM; 600.075 |
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Admin @ si @ GGM2015 |
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2614 |
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Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Title |
Quality Assessment of Optical Flow in Tagging MRI |
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2015 |
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5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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BME |
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IAM; ADAS; 600.076; 600.075 |
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Admin @ si @ KMF2015 |
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2616 |
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Olivier Lefebvre; Pau Riba; Charles Fournier; Alicia Fornes; Josep Llados; Rejean Plamondon; Jules Gagnon-Marchand |
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Monitoring neuromotricity on-line: a cloud computing approach |
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2015 |
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17th Conference of the International Graphonomics Society IGS2015 |
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The goal of our experiment is to develop a useful and accessible tool that can be used to evaluate a patient's health by analyzing handwritten strokes. We use a cloud computing approach to analyze stroke data sampled on a commercial tablet working on the Android platform and a distant server to perform complex calculations using the Delta and Sigma lognormal algorithms. A Google Drive account is used to store the data and to ease the development of the project. The communication between the tablet, the cloud and the server is encrypted to ensure biomedical information confidentiality. Highly parameterized biomedical tests are implemented on the tablet as well as a free drawing test to evaluate the validity of the data acquired by the first test compared to the second one. A blurred shape model descriptor pattern recognition algorithm is used to classify the data obtained by the free drawing test. The functions presented in this paper are still currently under development and other improvements are needed before launching the application in the public domain. |
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Pointe-à-Pitre; Guadeloupe; June 2015 |
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IGS |
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DAG; 600.077 |
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Admin @ si @ LRF2015 |
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2617 |
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Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta |
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Title |
Large-scale Graph Indexing using Binary Embeddings of Node Contexts |
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Conference Article |
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2015 |
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10th IAPR-TC15 Workshop on Graph-based Representations in Pattern Recognition |
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9069 |
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208-217 |
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Graph matching; Graph indexing; Application in document analysis; Word spotting; Binary embedding |
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Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations in terms of feature vectors. Retrieving a query graph from a large dataset of graphs has the drawback of the high computational complexity required to compare the query and the target graphs. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. In this paper we propose a fast indexation formalism for graph retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Hence, each attribute counts the length of a walk of order k originated in a vertex with label l. Each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in a handwritten word spotting scenario in images of historical documents. |
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Beijing; China; May 2015 |
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Springer International Publishing |
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C.-L.Liu; B.Luo; W.G.Kropatsch; J.Cheng |
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LNCS |
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0302-9743 |
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978-3-319-18223-0 |
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GbRPR |
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DAG; 600.061; 602.006; 600.077 |
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Admin @ si @ RLF2015a |
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2618 |
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Author |
R. Clariso; David Masip; A. Rius |
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Title |
Student projects empowering mobile learning in higher education |
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Journal |
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Year |
2014 |
Publication |
Revista de Universidad y Sociedad del Conocimiento |
Abbreviated Journal |
RUSC |
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11 |
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192-207 |
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1698-580X |
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OR;MV |
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no |
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Call Number |
Admin @ si @ CMR2014 |
Serial |
2619 |
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Author |
Joan Arnedo-Moreno; D. Bañeres; Xavier Baro; S. Caballe; S. Guerrero; L. Porta; J. Prieto |
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Title |
Va-ID: A trust-based virtual assessment system |
Type |
Conference Article |
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Year |
2014 |
Publication |
6th International Conference on Intelligent Networking and Collaborative Systems |
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328 - 335 |
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Abstract |
Even though online education is a very important pillar of lifelong education, institutions are still reluctant to wager for a fully online educational model. At the end, they keep relying on on-site assessment systems, mainly because fully virtual alternatives do not have the deserved social recognition or credibility. Thus, the design of virtual assessment systems that are able to provide effective proof of student authenticity and authorship and the integrity of the activities in a scalable and cost efficient manner would be very helpful. This paper presents ValID, a virtual assessment approach based on a continuous trust level evaluation between students and the institution. The current trust level serves as the main mechanism to dynamically decide which kind of controls a given student should be subjected to, across different courses in a degree. The main goal is providing a fair trade-off between security, scalability and cost, while maintaining the perceived quality of the educational model. |
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Salerna; Italy; September 2014 |
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978-1-4799-6386-7 |
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INCOS |
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OR; HuPBA;MV |
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Admin @ si @ ABB2014 |
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2620 |
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Author |
B. Zhou; Agata Lapedriza; J. Xiao; A. Torralba; A. Oliva |
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Title |
Learning Deep Features for Scene Recognition using Places Database |
Type |
Conference Article |
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Year |
2014 |
Publication |
28th Annual Conference on Neural Information Processing Systems |
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487-495 |
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Montreal; Canada; December 2014 |
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NIPS |
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OR;MV |
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no |
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Admin @ si @ ZLX2014 |
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2621 |
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