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Author | Firat Ismailoglu; Ida G. Sprinkhuizen-Kuyper; Evgueni Smirnov; Sergio Escalera; Ralf Peeters | ||||
Title | Fractional Programming Weighted Decoding for Error-Correcting Output Codes | Type | Conference Article | ||
Year | 2015 | Publication | Multiple Classifier Systems, Proceedings of 12th International Workshop , MCS 2015 | Abbreviated Journal | |
Volume | Issue | Pages | 38-50 | ||
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Abstract | 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. | ||||
Address | Gunzburg; Germany; June 2015 | ||||
Corporate Author | Thesis | ||||
Publisher | Springer International Publishing | Place of Publication | Editor | ||
Language | Summary Language | Original Title | |||
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ISSN | ISBN | 978-3-319-20247-1 | Medium | ||
Area | Expedition | Conference | MCS | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ ISS2015 | Serial | 2601 | ||
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Author | Hugo Jair Escalante; Jose Martinez; Sergio Escalera; Victor Ponce; Xavier Baro | ||||
Title | Improving Bag of Visual Words Representations with Genetic Programming | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
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Abstract | 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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Address | Killarney; Ireland; July 2015 | ||||
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Area | Expedition | Conference | IJCNN | ||
Notes | HuPBA;MV;OR | Approved | no | ||
Call Number | Admin @ si @ EME2015 | Serial | 2603 | ||
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Author | Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera; Tin Kam Ho; Nuria Macia; Bisakha Ray; Alexander Statnikov; Evelyne Viegas | ||||
Title | Design of the 2015 ChaLearn AutoML Challenge | Type | Conference Article | ||
Year | 2015 | Publication | IEEE International Joint Conference on Neural Networks IJCNN2015 | Abbreviated Journal | |
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Abstract | 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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Address | Killarney; Ireland; July 2015 | ||||
Corporate Author | Thesis | ||||
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Area | Expedition | Conference | IJCNN | ||
Notes | HuPBA;MILAB | Approved | no | ||
Call Number | Admin @ si @ GBC2015a | Serial | 2604 | ||
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Author | Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda | ||||
Title | PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities | Type | Journal | ||
Year | 2015 | Publication | Journal of Technology and Science Education | Abbreviated Journal | JOTSE |
Volume | 5 | Issue | 2 | Pages | 87-96 |
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Notes | IAM; ADAS; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ MRG2015 | Serial | 2608 | ||
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Author | Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; J.Roncaries; Debora Gil | ||||
Title | Automatic evaluation of practices in Moodle for Self Learning in Engineering | Type | Journal | ||
Year | 2015 | Publication | Journal of Technology and Science Education | Abbreviated Journal | JOTSE |
Volume | 5 | Issue | 2 | Pages | 97-106 |
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Notes | IAM; DAG; 600.075; 600.077 | Approved | no | ||
Call Number | Admin @ si @ SRM2015 | Serial | 2610 | ||
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Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Antoni Rosell; Marta Diez-Ferrer; Debora Gil | ||||
Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Journal Article | ||
Year | 2015 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCAR |
Volume | 10 | Issue | 6 | Pages | 935-945 |
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Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SBS2015a | Serial | 2611 | ||
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Author | Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell | ||||
Title | Quasi-real time digital assessment of Central Airway Obstruction | Type | Conference Article | ||
Year | 2015 | Publication | 3rd European congress for bronchology and interventional pulmonology ECBIP2015 | Abbreviated Journal | |
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Address | Barcelona; Spain; April 2015 | ||||
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Area | Expedition | Conference | ECBIP | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | SGT2015 | Serial | 2612 | ||
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Author | Carles Sanchez; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell; Debora Gil | ||||
Title | Towards On-line Quantification of Tracheal Stenosis from Videobronchoscopy | Type | Conference Article | ||
Year | 2015 | Publication | 6th International Conference on Information Processing in Computer-Assisted Interventions IPCAI2015 | Abbreviated Journal | |
Volume | 10 | Issue | 6 | Pages | 935-945 |
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Abstract | PURPOSE:
Lack of objective measurement of tracheal obstruction degree has a negative impact on the chosen treatment prone to lead to unnecessary repeated explorations and other scanners. Accurate computation of tracheal stenosis in videobronchoscopy would constitute a breakthrough for this noninvasive technique and a reduction in operation cost for the public health service. METHODS: Stenosis calculation is based on the comparison of the region delimited by the lumen in an obstructed frame and the region delimited by the first visible ring in a healthy frame. We propose a parametric strategy for the extraction of lumen and tracheal ring regions based on models of their geometry and appearance that guide a deformable model. To ensure a systematic applicability, we present a statistical framework to choose optimal parametric values and a strategy to choose the frames that minimize the impact of scope optical distortion. RESULTS: Our method has been tested in 40 cases covering different stenosed tracheas. Experiments report a non- clinically relevant [Formula: see text] of discrepancy in the calculated stenotic area and a computational time allowing online implementation in the operating room. CONCLUSIONS: Our methodology allows reliable measurements of airway narrowing in the operating room. To fully assess its clinical impact, a prospective clinical trial should be done. |
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Address | Barcelona; Spain; June 2015 | ||||
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ISSN | ISBN | Medium | |||
Area | Expedition | Conference | IPCAI | ||
Notes | IAM; MV; 600.075 | Approved | no | ||
Call Number | Admin @ si @ SBS2015b | Serial | 2613 | ||
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Author | Sergio Vera; Miguel Angel Gonzalez Ballester; Debora Gil | ||||
Title | A Novel Cochlear Reference Frame Based On The Laplace Equation | Type | Conference Article | ||
Year | 2015 | Publication | 29th international Congress and Exhibition on Computer Assisted Radiology and Surgery | Abbreviated Journal | |
Volume | 10 | Issue | 1 | Pages | 1-312 |
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Abstract | Poster | ||||
Address | Barcelona; Spain; June 2015 | ||||
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Area | Expedition | Conference | CARS | ||
Notes | IAM; 600.075 | Approved | no | ||
Call Number | Admin @ si @ VGG2015 | Serial | 2615 | ||
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Author | Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen | ||||
Title | Quality Assessment of Optical Flow in Tagging MRI | Type | Conference Article | ||
Year | 2015 | Publication | 5th Dutch Bio-Medical Engineering Conference BME2015 | Abbreviated Journal | |
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Address | The Netherlands; January 2015 | ||||
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Area | Expedition | Conference | BME | ||
Notes | IAM; ADAS; 600.076; 600.075 | Approved | no | ||
Call Number | Admin @ si @ KMF2015 | Serial | 2616 | ||
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Author | Olivier Lefebvre; Pau Riba; Charles Fournier; Alicia Fornes; Josep Llados; Rejean Plamondon; Jules Gagnon-Marchand | ||||
Title | Monitoring neuromotricity on-line: a cloud computing approach | Type | Conference Article | ||
Year | 2015 | Publication | 17th Conference of the International Graphonomics Society IGS2015 | Abbreviated Journal | |
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Abstract | 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. | ||||
Address | Pointe-à-Pitre; Guadeloupe; June 2015 | ||||
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Area | Expedition | Conference | IGS | ||
Notes | DAG; 600.077 | Approved | no | ||
Call Number | Admin @ si @ LRF2015 | Serial | 2617 | ||
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Author | Bogdan Raducanu; Alireza Bosaghzadeh; Fadi Dornaika | ||||
Title | Multi-observation Face Recognition in Videos based on Label Propagation | Type | Conference Article | ||
Year | 2015 | Publication | 6th Workshop on Analysis and Modeling of Faces and Gestures AMFG2015 | Abbreviated Journal | |
Volume | Issue | Pages | 10-17 | ||
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Abstract | In order to deal with the huge amount of content generated by social media, especially for indexing and retrieval purposes, the focus shifted from single object recognition to multi-observation object recognition. Of particular interest is the problem of face recognition (used as primary cue for persons’ identity assessment), since it is highly required by popular social media search engines like Facebook and Youtube. Recently, several approaches for graph-based label propagation were proposed. However, the associated graphs were constructed in an ad-hoc manner (e.g., using the KNN graph) that cannot cope properly with the rapid and frequent changes in data appearance, a phenomenon intrinsically related with video sequences. In this paper, we
propose a novel approach for efficient and adaptive graph construction, based on a two-phase scheme: (i) the first phase is used to adaptively find the neighbors of a sample and also to find the adequate weights for the minimization function of the second phase; (ii) in the second phase, the selected neighbors along with their corresponding weights are used to locally and collaboratively estimate the sparse affinity matrix weights. Experimental results performed on Honda Video Database (HVDB) and a subset of video sequences extracted from the popular TV-series ’Friends’ show a distinct advantage of the proposed method over the existing standard graph construction methods. |
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Address | Boston; USA; June 2015 | ||||
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Area | Expedition | Conference | CVPRW | ||
Notes | LAMP; 600.068; 600.072;;MV | Approved | no | ||
Call Number | Admin @ si @ RBD2015 | Serial | 2627 | ||
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Author | Marco Pedersoli; Andrea Vedaldi; Jordi Gonzalez; Xavier Roca | ||||
Title | A coarse-to-fine approach for fast deformable object detection | Type | Journal Article | ||
Year | 2015 | Publication | Pattern Recognition | Abbreviated Journal | PR |
Volume | 48 | Issue | 5 | Pages | 1844-1853 |
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Abstract | We present a method that can dramatically accelerate object detection with part based models. The method is based on the observation that the cost of detection is likely to be dominated by the cost of matching each part to the image, and not by the cost of computing the optimal configuration of the parts as commonly assumed. Therefore accelerating detection requires minimizing the number of
part-to-image comparisons. To this end we propose a multiple-resolutions hierarchical part based model and a corresponding coarse-to-fine inference procedure that recursively eliminates from the search space unpromising part placements. The method yields a ten-fold speedup over the standard dynamic programming approach and is complementary to the cascade-of-parts approach of [9]. Compared to the latter, our method does not have parameters to be determined empirically, which simplifies its use during the training of the model. Most importantly, the two techniques can be combined to obtain a very significant speedup, of two orders of magnitude in some cases. We evaluate our method extensively on the PASCAL VOC and INRIA datasets, demonstrating a very high increase in the detection speed with little degradation of the accuracy. |
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Notes | ISE; 600.078; 602.005; 605.001; 302.012 | Approved | no | ||
Call Number | Admin @ si @ PVG2015 | Serial | 2628 | ||
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Author | Cristhian A. Aguilera-Carrasco; Angel Sappa; Ricardo Toledo | ||||
Title | LGHD: a Feature Descriptor for Matching Across Non-Linear Intensity Variations | Type | Conference Article | ||
Year | 2015 | Publication | 22th IEEE International Conference on Image Processing | Abbreviated Journal | |
Volume | Issue | Pages | 178 - 181 | ||
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Address | Quebec; Canada; September 2015 | ||||
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Area | Expedition | Conference | ICIP | ||
Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ AST2015 | Serial | 2630 | ||
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Author | Jiaolong Xu | ||||
Title | Domain Adaptation of Deformable Part-based Models | Type | Book Whole | ||
Year | 2015 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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Abstract | On-board pedestrian detection is crucial for Advanced Driver Assistance Systems
(ADAS). An accurate classication is fundamental for vision-based pedestrian detection. The underlying assumption for learning classiers is that the training set and the deployment environment (testing) follow the same probability distribution regarding the features used by the classiers. However, in practice, there are dierent reasons that can break this constancy assumption. Accordingly, reusing existing classiers by adapting them from the previous training environment (source domain) to the new testing one (target domain) is an approach with increasing acceptance in the computer vision community. In this thesis we focus on the domain adaptation of deformable part-based models (DPMs) for pedestrian detection. As a prof of concept, we use a computer graphic based synthetic dataset, i.e. a virtual world, as the source domain, and adapt the virtual-world trained DPM detector to various real-world dataset. We start by exploiting the maximum detection accuracy of the virtual-world trained DPM. Even though, when operating in various real-world datasets, the virtualworld trained detector still suer from accuracy degradation due to the domain gap of virtual and real worlds. We then focus on domain adaptation of DPM. At the rst step, we consider single source and single target domain adaptation and propose two batch learning methods, namely A-SSVM and SA-SSVM. Later, we further consider leveraging multiple target (sub-)domains for progressive domain adaptation and propose a hierarchical adaptive structured SVM (HA-SSVM) for optimization. Finally, we extend HA-SSVM for the challenging online domain adaptation problem, aiming at making the detector to automatically adapt to the target domain online, without any human intervention. All of the proposed methods in this thesis do not require revisiting source domain data. The evaluations are done on the Caltech pedestrian detection benchmark. Results show that SA-SSVM slightly outperforms A-SSVM and avoids accuracy drops as high as 15 points when comparing with a non-adapted detector. The hierarchical model learned by HA-SSVM further boosts the domain adaptation performance. Finally, the online domain adaptation method has demonstrated that it can achieve comparable accuracy to the batch learned models while not requiring manually label target domain examples. Domain adaptation for pedestrian detection is of paramount importance and a relatively unexplored area. We humbly hope the work in this thesis could provide foundations for future work in this area. |
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Address | April 2015 | ||||
Corporate Author | Thesis | Ph.D. thesis | |||
Publisher | Place of Publication | Editor | Antonio Lopez | ||
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ISSN | ISBN | 978-84-943427-1-4 | Medium | ||
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Notes | ADAS; 600.076 | Approved | no | ||
Call Number | Admin @ si @ Xu2015 | Serial | 2631 | ||
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