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Zhen Xu; Sergio Escalera; Adrien Pavao; Magali Richard; Wei-Wei Tu; Quanming Yao; Huan Zhao; Isabelle Guyon |
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Title |
Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform |
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Journal Article |
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Year |
2022 |
Publication |
Patterns |
Abbreviated Journal |
PATTERNS |
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Volume |
3 |
Issue |
7 |
Pages |
100543 |
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Keywords |
Machine learning; data science; benchmark platform; reproducibility; competitions |
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Abstract |
Obtaining a standardized benchmark of computational methods is a major issue in data-science communities. Dedicated frameworks enabling fair benchmarking in a unified environment are yet to be developed. Here, we introduce Codabench, a meta-benchmark platform that is open sourced and community driven for benchmarking algorithms or software agents versus datasets or tasks. A public instance of Codabench is open to everyone free of charge and allows benchmark organizers to fairly compare submissions under the same setting (software, hardware, data, algorithms), with custom protocols and data formats. Codabench has unique features facilitating easy organization of flexible and reproducible benchmarks, such as the possibility of reusing templates of benchmarks and supplying compute resources on demand. Codabench has been used internally and externally on various applications, receiving more than 130 users and 2,500 submissions. As illustrative use cases, we introduce four diverse benchmarks covering graph machine learning, cancer heterogeneity, clinical diagnosis, and reinforcement learning. |
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June 24, 2022 |
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Science Direct |
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HuPBA |
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Admin @ si @ XEP2022 |
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3764 |
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Author |
Asma Bensalah; Alicia Fornes; Cristina Carmona_Duarte; Josep Llados |
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Title |
Easing Automatic Neurorehabilitation via Classification and Smoothness Analysis |
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Conference Article |
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Year |
2022 |
Publication |
Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 |
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13424 |
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336-348 |
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Neurorehabilitation; Upper-lim; Movement classification; Movement smoothness; Deep learning; Jerk |
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Assessing the quality of movements for post-stroke patients during the rehabilitation phase is vital given that there is no standard stroke rehabilitation plan for all the patients. In fact, it depends basically on the patient’s functional independence and its progress along the rehabilitation sessions. To tackle this challenge and make neurorehabilitation more agile, we propose an automatic assessment pipeline that starts by recognising patients’ movements by means of a shallow deep learning architecture, then measuring the movement quality using jerk measure and related measures. A particularity of this work is that the dataset used is clinically relevant, since it represents movements inspired from Fugl-Meyer a well common upper-limb clinical stroke assessment scale for stroke patients. We show that it is possible to detect the contrast between healthy and patients movements in terms of smoothness, besides achieving conclusions about the patients’ progress during the rehabilitation sessions that correspond to the clinicians’ findings about each case. |
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June 7-9, 2022, Las Palmas de Gran Canaria, Spain |
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IGS |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ BFC2022 |
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3738 |
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Alicia Fornes; Asma Bensalah; Cristina Carmona_Duarte; Jialuo Chen; Miguel A. Ferrer; Andreas Fischer; Josep Llados; Cristina Martin; Eloy Opisso; Rejean Plamondon; Anna Scius-Bertrand; Josep Maria Tormos |
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Title |
The RPM3D Project: 3D Kinematics for Remote Patient Monitoring |
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Conference Article |
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2022 |
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Intertwining Graphonomics with Human Movements. 20th International Conference of the International Graphonomics Society, IGS 2022 |
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13424 |
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217-226 |
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Healthcare applications; Kinematic; Theory of Rapid Human Movements; Human activity recognition; Stroke rehabilitation; 3D kinematics |
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This project explores the feasibility of remote patient monitoring based on the analysis of 3D movements captured with smartwatches. We base our analysis on the Kinematic Theory of Rapid Human Movement. We have validated our research in a real case scenario for stroke rehabilitation at the Guttmann Institute (https://www.guttmann.com/en/) (neurorehabilitation hospital), showing promising results. Our work could have a great impact in remote healthcare applications, improving the medical efficiency and reducing the healthcare costs. Future steps include more clinical validation, developing multi-modal analysis architectures (analysing data from sensors, images, audio, etc.), and exploring the application of our technology to monitor other neurodegenerative diseases. |
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June 7-9, 2022, Las Palmas de Gran Canaria, Spain |
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DAG; 600.121; 600.162; 602.230; 600.140 |
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Admin @ si @ FBC2022 |
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3739 |
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Author |
German Ros; J. Guerrero; Angel Sappa; Antonio Lopez |
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Title |
VSLAM pose initialization via Lie groups and Lie algebras optimization |
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Conference Article |
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Year |
2013 |
Publication |
Proceedings of IEEE International Conference on Robotics and Automation |
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5740 - 5747 |
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SLAM |
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We present a novel technique for estimating initial 3D poses in the context of localization and Visual SLAM problems. The presented approach can deal with noise, outliers and a large amount of input data and still performs in real time in a standard CPU. Our method produces solutions with an accuracy comparable to those produced by RANSAC but can be much faster when the percentage of outliers is high or for large amounts of input data. On the current work we propose to formulate the pose estimation as an optimization problem on Lie groups, considering their manifold structure as well as their associated Lie algebras. This allows us to perform a fast and simple optimization at the same time that conserve all the constraints imposed by the Lie group SE(3). Additionally, we present several key design concepts related with the cost function and its Jacobian; aspects that are critical for the good performance of the algorithm. |
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Karlsruhe; Germany; May 2013 |
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1050-4729 |
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978-1-4673-5641-1 |
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ICRA |
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ADAS; 600.054; 600.055; 600.057 |
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Admin @ si @ RGS2013a; ADAS @ adas @ |
Serial |
2225 |
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Author |
Sergio Escalera; Jordi Gonzalez; Xavier Baro; Pablo Pardo; Junior Fabian; Marc Oliu; Hugo Jair Escalante; Ivan Huerta; Isabelle Guyon |
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Title |
ChaLearn Looking at People 2015 new competitions: Age Estimation and Cultural Event Recognition |
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Conference Article |
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2015 |
Publication |
IEEE International Joint Conference on Neural Networks IJCNN2015 |
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1-8 |
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Following previous series on Looking at People (LAP) challenges [1], [2], [3], in 2015 ChaLearn runs two new competitions within the field of Looking at People: age and cultural event recognition in still images. We propose thefirst crowdsourcing application to collect and label data about apparent
age of people instead of the real age. In terms of cultural event recognition, tens of categories have to be recognized. This involves scene understanding and human analysis. This paper summarizes both challenges and data, providing some initial baselines. The results of the first round of the competition were presented at ChaLearn LAP 2015 IJCNN special session on computer vision and robotics http://www.dtic.ua.es/∼jgarcia/IJCNN2015.
Details of the ChaLearn LAP competitions can be found at http://gesture.chalearn.org/. |
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Killarney; Ireland; July 2015 |
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IJCNN |
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HuPBA; ISE; 600.063; 600.078;MV |
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no |
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Admin @ si @ EGB2015 |
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2591 |
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Author |
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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Year |
2015 |
Publication |
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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no |
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Admin @ si @ EME2015 |
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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 |
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Title |
Design of the 2015 ChaLearn AutoML Challenge |
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Conference Article |
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Year |
2015 |
Publication |
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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no |
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Admin @ si @ GBC2015a |
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2604 |
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Author |
Isabelle Guyon; Kristin Bennett; Gavin Cawley; Hugo Jair Escalante; Sergio Escalera |
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Title |
The AutoML challenge on codalab |
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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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Killarney; Ireland; July 2015 |
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IJCNN |
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HuPBA;MILAB |
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Admin @ si @ GBC2015b |
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2650 |
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Author |
Gerard Canal; Cecilio Angulo; Sergio Escalera |
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Title |
Gesture based Human Multi-Robot interaction |
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Conference Article |
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2015 |
Publication |
IEEE International Joint Conference on Neural Networks IJCNN2015 |
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The emergence of robot applications for nontechnical users implies designing new ways of interaction between robotic platforms and users. The main goal of this work is the development of a gestural interface to interact with robots
in a similar way as humans do, allowing the user to provide information of the task with non-verbal communication. The gesture recognition application has been implemented using the Microsoft’s KinectTM v2 sensor. Hence, a real-time algorithm based on skeletal features is described to deal with both, static
gestures and dynamic ones, being the latter recognized using a weighted Dynamic Time Warping method. The gesture recognition application has been implemented in a multi-robot case.
A NAO humanoid robot is in charge of interacting with the users and respond to the visual signals they produce. Moreover, a wheeled Wifibot robot carries both the sensor and the NAO robot, easing navigation when necessary. A broad set of user tests have been carried out demonstrating that the system is, indeed, a
natural approach to human robot interaction, with a fast response and easy to use, showing high gesture recognition rates. |
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Killarney; Ireland; July 2015 |
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IJCNN |
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HuPBA;MILAB |
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CAE2015a |
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2651 |
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Author |
Partha Pratim Roy; Josep Llados; Umapada Pal |
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Text/Graphics Separation in Color Maps |
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2007 |
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International Conference on Computing: Theory and Applications |
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545–551 |
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Kolkata (India) |
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DAG @ dag @ RLP2007a |
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806 |
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Oriol Ramos Terrades; Salvatore Tabbone; Ernest Valveny |
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Optimal Linear Combination for Two-class Classifiers |
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2007 |
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Proceedings of the International Conference on Advances in Pattern Recognition |
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Kolkata (India) |
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DAG |
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DAG @ dag @ RTV2007a |
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894 |
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Alicia Fornes; Josep Llados |
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A Symbol-dependent Writer Identifcation Approach in Old Handwritten Music Scores |
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2010 |
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12th International Conference on Frontiers in Handwriting Recognition |
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634 - 639 |
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Writer identification consists in determining the writer of a piece of handwriting from a set of writers. In this paper we introduce a symbol-dependent approach for identifying the writer of old music scores, which is based on two symbol recognition methods. The main idea is to use the Blurred Shape Model descriptor and a DTW-based method for detecting, recognizing and describing the music clefs and notes. The proposed approach has been evaluated in a database of old music scores, achieving very high writer identification rates. |
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Kolkata (India) |
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978-1-4244-8353-2 |
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ICFHR |
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DAG |
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DAG @ dag @ FoL2010 |
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1321 |
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Author |
Fernando Vilariño |
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Bringing and keeping all the stakeholders together: creating a catalog of models of governance for innovation |
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Miscellaneous |
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2017 |
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Open Living Lab Days Report |
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Krakow; August 2017 |
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MV; no menciona;SIAI |
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Call Number |
Admin @ si @ Vil2017b |
Serial |
3033 |
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Author |
Zhong Jin; Franck Davoine |
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Title |
Orthogonal ICA Representation Of Images |
Type |
Miscellaneous |
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Year |
2004 |
Publication |
8th International Conference on Control, Automation, Robotics and Vision, 369–374 |
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Address |
Kunming (China) |
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Approved |
no |
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Call Number |
Admin @ si @ JiD2004 |
Serial |
499 |
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Author |
Xavier Boix; Josep M. Gonfaus; Fahad Shahbaz Khan; Joost Van de Weijer; Andrew Bagdanov; Marco Pedersoli; Jordi Gonzalez; Joan Serrat |
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Title |
Combining local and global bag-of-word representations for semantic segmentation |
Type |
Conference Article |
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Year |
2009 |
Publication |
Workshop on The PASCAL Visual Object Classes Challenge |
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Address |
Kyoto (Japan) |
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ICCV |
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Notes |
ADAS;ISE |
Approved |
no |
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Call Number |
ADAS @ adas @ BGS2009 |
Serial |
1273 |
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| Permanent link to this record |
