| Records |
| Author |
Fernando Barrera; Felipe Lumbreras; Cristhian Aguilera; Angel Sappa |
| Title |
Planar-Based Multispectral Stereo |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Address |
Naples, Italy |
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Expedition |
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Conference |
QIRT |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ BLA2012 |
Serial |
2016 |
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| Author |
Cristhian Aguilera; Fernando Barrera; Angel Sappa; Ricardo Toledo |
| Title |
A Novel SIFT-Like-Based Approach for FIR-VS Images Registration |
Type |
Conference Article |
| Year |
2012 |
Publication |
11th Quantitative InfraRed Thermography |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Address |
Naples, Italy |
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Conference |
QIRT |
| Notes |
ADAS; TV |
Approved |
no |
| Call Number |
Admin @ si @ ABS2012 |
Serial |
2017 |
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| Author |
Monica Piñol; Angel Sappa; Angeles Lopez; Ricardo Toledo |
| Title |
Feature Selection Based on Reinforcement Learning for Object Recognition |
Type |
Conference Article |
| Year |
2012 |
Publication |
Adaptive Learning Agents Workshop |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
33-39 |
| Keywords |
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| Abstract |
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| Address |
Valencia |
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Conference |
ALA |
| Notes |
ADAS; RV |
Approved |
no |
| Call Number |
Admin @ si @ PSL2012 |
Serial |
2018 |
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| Author |
German Ros; Angel Sappa; Daniel Ponsa; Antonio Lopez |
| Title |
Visual SLAM for Driverless Cars: A Brief Survey |
Type |
Conference Article |
| Year |
2012 |
Publication |
IEEE Workshop on Navigation, Perception, Accurate Positioning and Mapping for Intelligent Vehicles |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
SLAM |
| Abstract |
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| Address |
Alcalá de Henares |
| Corporate Author |
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Place of Publication |
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Summary Language |
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Original Title |
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Conference |
IVW |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RSP2012; ADAS @ adas |
Serial |
2019 |
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| Author |
Naila Murray; Luca Marchesotti; Florent Perronnin |
| Title |
Learning to Rank Images using Semantic and Aesthetic Labels |
Type |
Conference Article |
| Year |
2012 |
Publication |
23rd British Machine Vision Conference |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
110.1-110.10 |
| Keywords |
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| Abstract |
Most works on image retrieval from text queries have addressed the problem of retrieving semantically relevant images. However, the ability to assess the aesthetic quality of an image is an increasingly important differentiating factor for search engines. In this work, given a semantic query, we are interested in retrieving images which are semantically relevant and score highly in terms of aesthetics/visual quality. We use large-margin classifiers and rankers to learn statistical models capable of ordering images based on the aesthetic and semantic information. In particular, we compare two families of approaches: while the first one attempts to learn a single ranker which takes into account both semantic and aesthetic information, the second one learns separate semantic and aesthetic models. We carry out a quantitative and qualitative evaluation on a recently-published large-scale dataset and we show that the second family of techniques significantly outperforms the first one. |
| Address |
Guildford, London |
| Corporate Author |
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Thesis |
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Place of Publication |
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Edition |
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ISBN |
1-901725-46-4 |
Medium |
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| Area |
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Expedition |
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Conference |
BMVC |
| Notes |
CIC |
Approved |
no |
| Call Number |
Admin @ si @ MMP2012b |
Serial |
2027 |
| Permanent link to this record |
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| Author |
Jose Carlos Rubio; Joan Serrat; Antonio Lopez |
| Title |
Multiple target tracking and identity linking under split, merge and occlusion of targets and observations |
Type |
Conference Article |
| Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Address |
Algarve, Portugal |
| Corporate Author |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICPRAM |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ RSL2012c; ADAS @ adas |
Serial |
2034 |
| Permanent link to this record |
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| Author |
Ferran Diego; G.D. Evangelidis; Joan Serrat |
| Title |
Night-time outdoor surveillance by mobile cameras |
Type |
Conference Article |
| Year |
2012 |
Publication |
1st International Conference on Pattern Recognition Applications and Methods |
Abbreviated Journal |
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| Volume |
2 |
Issue |
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Pages |
365-371 |
| Keywords |
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| Abstract |
This paper addresses the problem of video surveillance by mobile cameras. We present a method that allows online change detection in night-time outdoor surveillance. Because of the camera movement, background frames are not available and must be “localized” in former sequences and registered with the current frames. To this end, we propose a Frame Localization And Registration (FLAR) approach that solves the problem efficiently. Frames of former sequences define a database which is queried by current frames in turn. To quickly retrieve nearest neighbors, database is indexed through a visual dictionary method based on the SURF descriptor. Furthermore, the frame localization is benefited by a temporal filter that exploits the temporal coherence of videos. Next, the recently proposed ECC alignment scheme is used to spatially register the synchronized frames. Finally, change detection methods apply to aligned frames in order to mark suspicious areas. Experiments with real night sequences recorded by in-vehicle cameras demonstrate the performance of the proposed method and verify its efficiency and effectiveness against other methods. |
| Address |
Algarve, Portugal |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICPRAM |
| Notes |
ADAS |
Approved |
no |
| Call Number |
Admin @ si @ DES2012 |
Serial |
2035 |
| Permanent link to this record |
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| |
| Author |
Cesar Isaza; Joaquin Salas; Bogdan Raducanu |
| Title |
Synthetic ground truth dataset to detect shadow cast by static objects in outdoor |
Type |
Conference Article |
| Year |
2012 |
Publication |
1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
art. 11 |
| Keywords |
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| Abstract |
In this paper, we propose a precise synthetic ground truth dataset to study the problem of detection of the shadows cast by static objects in outdoor environments during extended periods of time (days). For our dataset, we have created a virtual scenario using a rendering software. To increase the realism of the simulated environment, we have defined the scenario in a precise geographical location. In our dataset the sun is by far the main illumination source. The sun position during the simulation time takes into consideration factors related to the geographical location, such as the latitude, longitude, elevation above sea level, and precise image capturing day and time. In our simulation the camera remains fixed. The dataset consists of seven days of simulation, from 10:00am to 5:00pm. Images are captured every 10 seconds. The shadows' ground truth is automatically computed by the rendering software. |
| Address |
Capri, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
ACM |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4503-1405-3 |
Medium |
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| Area |
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Expedition |
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Conference |
VIGTA |
| Notes |
OR;MV |
Approved |
no |
| Call Number |
Admin @ si @ ISR2012a |
Serial |
2037 |
| Permanent link to this record |
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| Author |
Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
| Title |
Supervised Brain Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder |
Type |
Conference Article |
| Year |
2012 |
Publication |
High Performance Computing and Simulation, International Conference on |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
182-187 |
| Keywords |
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| Abstract |
This paper presents an automatic method for external and internal segmentation of the caudate nucleus in Magnetic Resonance Images (MRI) based on statistical and structural machine learning approaches. This method is applied in Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis. The external segmentation method adapts the Graph Cut energy-minimization model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus. In particular, new energy function data and boundary potentials are defined and a supervised energy term based on contextual brain structures is added. Furthermore, the internal segmentation method learns a classifier based on shape features of the Region of Interest (ROI) in MRI slices. The results show accurate external and internal caudate segmentation in a real data set and similar performance of ADHD diagnostic test to manual annotation. |
| Address |
Madrid |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4673-2359-8 |
Medium |
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| Area |
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Expedition |
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Conference |
HPCS |
| Notes |
MILAB;HuPBA |
Approved |
no |
| Call Number |
Admin @ si @ ISH2012a |
Serial |
2038 |
| Permanent link to this record |
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| Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
| Title |
Three-Dimensional Design of Error Correcting Output Codes |
Type |
Conference Article |
| Year |
2012 |
Publication |
8th International Conference on Machine Learning and Data Mining |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
29- |
| Keywords |
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| Abstract |
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| Address |
Berlin, Germany |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
MLDM |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ BGE2012a |
Serial |
2041 |
| Permanent link to this record |
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| Author |
Mohammad Ali Bagheri; Qigang Gao; Sergio Escalera |
| Title |
Error Correcting Output Codes for multiclass classification: Application to two image vision problems |
Type |
Conference Article |
| Year |
2012 |
Publication |
16th symposium on Artificial Intelligence & Signal Processing |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
508-513 |
| Keywords |
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| Abstract |
Error-correcting output codes (ECOC) represents a powerful framework to deal with multiclass classification problems based on combining binary classifiers. The key factor affecting the performance of ECOC methods is the independence of binary classifiers, without which the ECOC method would be ineffective. In spite of its ability on classification of problems with relatively large number of classes, it has been applied in few real world problems. In this paper, we investigate the behavior of the ECOC approach on two image vision problems: logo recognition and shape classification using Decision Tree and AdaBoost as the base learners. The results show that the ECOC method can be used to improve the classification performance in comparison with the classical multiclass approaches. |
| Address |
Shiraz, Iran |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Xplore |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4673-1478-7 |
Medium |
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| Area |
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Expedition |
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Conference |
AISP |
| Notes |
HuPBA;MILAB |
Approved |
no |
| Call Number |
Admin @ si @ BGE2012b |
Serial |
2042 |
| Permanent link to this record |
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| Author |
Albert Gordo; Florent Perronnin; Ernest Valveny |
| Title |
Document classification using multiple views |
Type |
Conference Article |
| Year |
2012 |
Publication |
10th IAPR International Workshop on Document Analysis Systems |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
33-37 |
| Keywords |
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| Abstract |
The combination of multiple features or views when representing documents or other kinds of objects usually leads to improved results in classification (and retrieval) tasks. Most systems assume that those views will be available both at training and test time. However, some views may be too `expensive' to be available at test time. In this paper, we consider the use of Canonical Correlation Analysis to leverage `expensive' views that are available only at training time. Experimental results show that this information may significantly improve the results in a classification task. |
| Address |
Australia |
| Corporate Author |
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Thesis |
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| Publisher |
IEEE Computer Society Washington |
Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-0-7695-4661-2 |
Medium |
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| Area |
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Expedition |
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Conference |
DAS |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GPV2012 |
Serial |
2049 |
| Permanent link to this record |
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| Author |
Francisco Cruz; Oriol Ramos Terrades |
| Title |
Document segmentation using relative location features |
Type |
Conference Article |
| Year |
2012 |
Publication |
21st International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1562-1565 |
| Keywords |
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| Abstract |
In this paper we evaluate the use of Relative Location Features (RLF) on a historical document segmentation task, and compare the quality of the results obtained on structured and unstructured documents using RLF and not using them. We prove that using these features improve the final segmentation on documents with a strong structure, while their application on unstructured documents does not show significant improvement. Although this paper is not focused on segmenting unstructured documents, results obtained on a benchmark dataset are equal or even overcome previous results of similar works. |
| Address |
Tsukuba Science City, Japan |
| Corporate Author |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ CrR2012 |
Serial |
2051 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; Josep Llados |
| Title |
The Role of the Users in Handwritten Word Spotting Applications: Query Fusion and Relevance Feedback |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
55-60 |
| Keywords |
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| Abstract |
In this paper we present the importance of including the user in the loop in a handwritten word spotting framework. Several off-the-shelf query fusion and relevance feedback strategies have been tested in the handwritten word spotting context. The increase in terms of precision when the user is included in the loop is assessed using two datasets of historical handwritten documents and a baseline word spotting approach based on a bag-of-visual-words model. |
| Address |
Bari, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4673-2262-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RuL2012 |
Serial |
2054 |
| Permanent link to this record |
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| Author |
Emanuel Indermühle; Volkmar Frinken; Horst Bunke |
| Title |
Mode Detection in Online Handwritten Documents using BLSTM Neural Networks |
Type |
Conference Article |
| Year |
2012 |
Publication |
13th International Conference on Frontiers in Handwriting Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
302-307 |
| Keywords |
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| Abstract |
Mode detection in online handwritten documents refers to the process of distinguishing different types of contents, such as text, formulas, diagrams, or tables, one from another. In this paper a new approach to mode detection is proposed that uses bidirectional long-short term memory (BLSTM) neural networks. The BLSTM neural network is a novel type of recursive neural network that has been successfully applied in speech and handwriting recognition. In this paper we show that it has the potential to significantly outperform traditional methods for mode detection, which are usually based on stroke classification. As a further advantage over previous approaches, the proposed system is trainable and does not rely on user-defined heuristics. Moreover, it can be easily adapted to new or additional types of modes by just providing the system with new training data. |
| Address |
Bari, italy |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-1-4673-2262-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICFHR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ IFB2012 |
Serial |
2056 |
| Permanent link to this record |
