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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Francesco Ciompi |
![find record details (via OpenURL) openurl](img/xref.gif)
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Title |
ECOC-based Plaque Classification using In-vivo and Exvivo Intravascular Ultrasound Data |
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2008 |
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CVC Technical Report #125 |
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Bellaterra (Spain) |
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Admin @ si @ Cio2008 |
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1145 |
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Francesco Fabbri; Xianghang Liu; Jack R. McKenzie; Bartlomiej Twardowski; Tri Kurniawan Wijaya |
![download PDF file pdf](img/file_PDF.gif)
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Title |
FedFNN: Faster Training Convergence Through Update Predictions in Federated Recommender Systems |
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2023 |
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ARXIV |
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Federated Learning (FL) has emerged as a key approach for distributed machine learning, enhancing online personalization while ensuring user data privacy. Instead of sending private data to a central server as in traditional approaches, FL decentralizes computations: devices train locally and share updates with a global server. A primary challenge in this setting is achieving fast and accurate model training – vital for recommendation systems where delays can compromise user engagement. This paper introduces FedFNN, an algorithm that accelerates decentralized model training. In FL, only a subset of users are involved in each training epoch. FedFNN employs supervised learning to predict weight updates from unsampled users, using updates from the sampled set. Our evaluations, using real and synthetic data, show: 1. FedFNN achieves training speeds 5x faster than leading methods, maintaining or improving accuracy; 2. the algorithm's performance is consistent regardless of client cluster variations; 3. FedFNN outperforms other methods in scenarios with limited client availability, converging more quickly. |
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LAMP |
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Admin @ si @ FLM2023 |
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3980 |
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Francisco Cruz; Oriol Ramos Terrades |
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Title |
A probabilistic framework for handwritten text line segmentation |
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2018 |
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Arxiv |
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Document Analysis; Text Line Segmentation; EM algorithm; Probabilistic Graphical Models; Parameter Learning |
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We successfully combine Expectation-Maximization algorithm and variational
approaches for parameter learning and computing inference on Markov random fields. This is a general method that can be applied to many computer
vision tasks. In this paper, we apply it to handwritten text line segmentation.
We conduct several experiments that demonstrate that our method deal with
common issues of this task, such as complex document layout or non-latin
scripts. The obtained results prove that our method achieve state-of-theart performance on different benchmark datasets without any particular fine
tuning step. |
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DAG; 600.097; 600.121 |
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Admin @ si @ CrR2018 |
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3253 |
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Francisco Javier Orozco; Pau Baiget; Jordi Gonzalez; Xavier Roca |
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Eyelids and Face Tracking in Real-Time |
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2006 |
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6th IASTED International Conference Visualization, Imaging, and Image Processing (VIIP´06), 165–170 |
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Palma de Mallorca (Spain) |
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ISE |
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ISE @ ise @ OBG2006 |
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730 |
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G.Estape; Enric Marti |
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L’ús d’aplicacions de visualització 3D com a eina d’aprenenetatge en activitats formatives dirigides i autònomes: el cas del programa Bluestar |
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2008 |
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V Jornades d’Innovació Docent UAB |
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IAM |
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IAM @ iam @ ESM2008 |
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1495 |
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Gabriel Villalonga; Sebastian Ramos; German Ros; David Vazquez; Antonio Lopez |
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Title |
3d Pedestrian Detection via Random Forest |
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2014 |
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European Conference on Computer Vision |
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231-238 |
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Pedestrian Detection |
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Our demo focuses on showing the extraordinary performance of our novel 3D pedestrian detector along with its simplicity and real-time capabilities. This detector has been designed for autonomous driving applications, but it can also be applied in other scenarios that cover both outdoor and indoor applications.
Our pedestrian detector is based on the combination of a random forest classifier with HOG-LBP features and the inclusion of a preprocessing stage based on 3D scene information in order to precisely determinate the image regions where the detector should search for pedestrians. This approach ends up in a high accurate system that runs real-time as it is required by many computer vision and robotics applications. |
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Zurich; suiza; September 2014 |
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ECCV-Demo |
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ADAS; 600.076 |
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Admin @ si @ VRR2014 |
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2570 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Gemma Sanchez; Ernest Valveny; Josep Llados; Joan Mas; N. Lozano |
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A platform to extract knowledge from graphic documents. Application to an architectural sketch understanding scenario |
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2004 |
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Document Analysis Systems VI, S. Marinai, A. Dengel (Eds.) Lecture Notes in Computer Science, 3163:389–400 |
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Springer-Verlag |
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DAG |
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DAG @ dag @ SVL2004 |
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460 |
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Gemma Sanchez; Josep Llados |
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Title |
A Graph Grammar to Recognize Textured Symbols. |
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2001 |
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Sixth International Conference on Document Analysis and Recognition, ICDAR 2001, 465–469. |
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USA |
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DAG |
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DAG @ dag @ SLl2001 |
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162 |
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Gemma Sanchez; Josep Llados |
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Syntactic models to represent perceptually regular repetitive patterns in graphic documents |
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2003 |
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Proceedings of Fifth IAPR International Workshop on Graphics Recognition, 194–201 |
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Barcelona |
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DAG |
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DAG @ dag @ SaL2003 |
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417 |
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Gemma Sanchez; Josep Llados |
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Syntactic models to represent perceptually regular repetitive patterns in graphic documents |
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2004 |
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Graphics Recognition: Recent Advances and Perspectives, Lecture Notes in Computer Science, J. Llados, Y.B. Kwon (Eds.), 3088:162–171 |
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DAG |
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DAG @ dag @ SaL2004 |
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462 |
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Author ![sorted by Author field, ascending order (up)](img/sort_asc.gif) |
Gemma Sanchez; Josep Llados; K. Tombre |
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An Algorithm to Recognize Graphical Textured Symbols using String Representations. |
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2001 |
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Proceedings of the IX Spanish Symposium on Pattern Recognition and Image Analysis, :203–208. |
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DAG |
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DAG @ dag @ SLT2001a |
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163 |
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Gemma Sanchez; Josep Llados; K. Tombre |
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Title |
An Error-Correction Graph Grammar to Recognize Textured Symbols. |
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2001 |
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Fourth IAPR International Workshop on Graphics Recognition, GREC 2001, 135–146. |
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Canada |
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DAG @ dag @ SLT2001b |
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164 |
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Georg Langs; Petia Radeva; David Rotger; Francesc Carreras |
![goto web page url](img/www.gif)
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Building and Registering Parameterized 3D Models of Vessel Trees for Visualization during Intervention |
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2004 |
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17th International Conference on Pattern Recognition, ICPR’04 |
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Cambridge, United Kingdom |
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MILAB |
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BCNPCL @ bcnpcl @ LRR2004b |
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463 |
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Georg Langs; Petia Radeva; David Rotger; Francesc Carreras |
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Explorative Building of 3D Vessel Tree Models |
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2004 |
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“Digital Imaging in Media and Education”, 28th annual workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) |
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Hagenberg (Austria) |
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MILAB |
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BCNPCL @ bcnpcl @ LRR2004a |
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467 |
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George A. Triantafyllid; Nikolaos Thomos; Cristina Cañero; P. Vieyres; Michael G. Strintzis |
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A User Interface for Mobile Robotized Tele-Echography |
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2005 |
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3rd International Conference on Imaging Technologies in Biomedical Sciences (ITBS 2005) |
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Milos Island (Greece) |
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Admin @ si @ TTC2005 |
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