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Author Mustafa Hajij; Mathilde Papillon; Florian Frantzen; Jens Agerberg; Ibrahem AlJabea; Ruben Ballester; Claudio Battiloro; Guillermo Bernardez; Tolga Birdal; Aiden Brent; Peter Chin; Sergio Escalera; Simone Fiorellino; Odin Hoff Gardaa; Gurusankar Gopalakrishnan; Devendra Govil; Josef Hoppe; Maneel Reddy Karri; Jude Khouja; Manuel Lecha; Neal Livesay; Jan Meibner; Soham Mukherjee; Alexander Nikitin; Theodore Papamarkou; Jaro Prilepok; Karthikeyan Natesan Ramamurthy; Paul Rosen; Aldo Guzman-Saenz; Alessandro Salatiello; Shreyas N. Samaga; Simone Scardapane; Michael T. Schaub; Luca Scofano; Indro Spinelli; Lev Telyatnikov; Quang Truong; Robin Walters; Maosheng Yang; Olga Zaghen; Ghada Zamzmi; Ali Zia; Nina Miolane
Title TopoX: A Suite of Python Packages for Machine Learning on Topological Domains Type Miscellaneous
Year 2024 Publication Arxiv Abbreviated Journal
Volume Issue Pages
Keywords
Abstract We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; TopoEmbedX provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; TopoModelx is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of TopoX is available under MIT license at this https URL.
Address
Corporate Author Thesis
Publisher Place of Publication (up) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HUPBA Approved no
Call Number Admin @ si @ HPF2024 Serial 4021
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Author German Barquero; Sergio Escalera; Cristina Palmero
Title Seamless Human Motion Composition with Blended Positional Encodings Type Miscellaneous
Year 2024 Publication Arxiv Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Conditional human motion generation is an important topic with many applications in virtual reality, gaming, and robotics. While prior works have focused on generating motion guided by text, music, or scenes, these typically result in isolated motions confined to short durations. Instead, we address the generation of long, continuous sequences guided by a series of varying textual descriptions. In this context, we introduce FlowMDM, the first diffusion-based model that generates seamless Human Motion Compositions (HMC) without any postprocessing or redundant denoising steps. For this, we introduce the Blended Positional Encodings, a technique that leverages both absolute and relative positional encodings in the denoising chain. More specifically, global motion coherence is recovered at the absolute stage, whereas smooth and realistic transitions are built at the relative stage. As a result, we achieve state-of-the-art results in terms of accuracy, realism, and smoothness on the Babel and HumanML3D datasets. FlowMDM excels when trained with only a single description per motion sequence thanks to its Pose-Centric Cross-ATtention, which makes it robust against varying text descriptions at inference time. Finally, to address the limitations of existing HMC metrics, we propose two new metrics: the Peak Jerk and the Area Under the Jerk, to detect abrupt transitions.
Address
Corporate Author Thesis
Publisher Place of Publication (up) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes HUPBA Approved no
Call Number Admin @ si @ BEP2024 Serial 4022
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Author Ayan Banerjee; Sanket Biswas; Josep Llados; Umapada Pal
Title GraphKD: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation Type Miscellaneous
Year 2024 Publication Arxiv Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Object detection in documents is a key step to automate the structural elements identification process in a digital or scanned document through understanding the hierarchical structure and relationships between different elements. Large and complex models, while achieving high accuracy, can be computationally expensive and memory-intensive, making them impractical for deployment on resource constrained devices. Knowledge distillation allows us to create small and more efficient models that retain much of the performance of their larger counterparts. Here we present a graph-based knowledge distillation framework to correctly identify and localize the document objects in a document image. Here, we design a structured graph with nodes containing proposal-level features and edges representing the relationship between the different proposal regions. Also, to reduce text bias an adaptive node sampling strategy is designed to prune the weight distribution and put more weightage on non-text nodes. We encode the complete graph as a knowledge representation and transfer it from the teacher to the student through the proposed distillation loss by effectively capturing both local and global information concurrently. Extensive experimentation on competitive benchmarks demonstrates that the proposed framework outperforms the current state-of-the-art approaches. The code will be available at: this https URL.
Address
Corporate Author Thesis
Publisher Place of Publication (up) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG Approved no
Call Number Admin @ si @ BBL2024b Serial 4023
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Author Tao Wu; Kai Wang; Chuanming Tang; Jianlin Zhang
Title Diffusion-based network for unsupervised landmark detection Type Journal Article
Year 2024 Publication Knowledge-Based Systems Abbreviated Journal
Volume 292 Issue Pages 111627
Keywords
Abstract Landmark detection is a fundamental task aiming at identifying specific landmarks that serve as representations of distinct object features within an image. However, the present landmark detection algorithms often adopt complex architectures and are trained in a supervised manner using large datasets to achieve satisfactory performance. When faced with limited data, these algorithms tend to experience a notable decline in accuracy. To address these drawbacks, we propose a novel diffusion-based network (DBN) for unsupervised landmark detection, which leverages the generation ability of the diffusion models to detect the landmark locations. In particular, we introduce a dual-branch encoder (DualE) for extracting visual features and predicting landmarks. Additionally, we lighten the decoder structure for faster inference, referred to as LightD. By this means, we avoid relying on extensive data comparison and the necessity of designing complex architectures as in previous methods. Experiments on CelebA, AFLW, 300W and Deepfashion benchmarks have shown that DBN performs state-of-the-art compared to the existing methods. Furthermore, DBN shows robustness even when faced with limited data cases.
Address
Corporate Author Thesis
Publisher Place of Publication (up) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes LAMP Approved no
Call Number Admin @ si @ WWT2024 Serial 4024
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Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
Year 2005 Publication ESC Congress Abbreviated Journal
Volume Issue Pages
Keywords Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
Abstract Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Address Stockholm; Sweden; September 2005
Corporate Author Thesis
Publisher Place of Publication (up) ,Sweden (EU) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference ESC
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RMF2005a Serial 1523
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Author Aura Hernandez-Sabate
Title Automatic adventitia segmentation in IntraVascular UltraSound images Type Report
Year 2005 Publication CVC Technical Report Abbreviated Journal
Volume Issue 85 Pages
Keywords
Abstract A usual tool in cardiac disease diagnosis is vessel plaque assessment by analysis of IVUS sequences. Manual detection of lumen-intima, intima-media and media-adventitia vessel borders is the main activity of physicians in the process of plaque quantification. Large variety in vessel border descriptors, as well as, shades, artifacts and blurred response due to ultrasound physical properties troubles automated media-adventitia segmentation. This experimental work presents a solution to such a complex problem. The process blends advanced anisotropic filtering operators and statistic classification techniques, achieving an efficient vessel border modelling strategy. First of all, we introduce the theoretic base of the method. After that, we show the steps of the algorithm, validating the method with statistics that show that the media-adventitia border detection achieves an accuracy in the range of inter-observer variability regardless of plaque nature, vessel geometry and incomplete vessel borders. Finally, we present a little Matlab application to the automatic media-adventitia border.
Address
Corporate Author Thesis Master's thesis
Publisher Place of Publication (up) 08193 Bellaterra, Barcelona (Spain) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ Her2005 Serial 1544
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Author Ferran Poveda
Title Visualització i interpretació tridimensional de l’arquitectura de les fibres musculars del miocardi Type Report
Year 2009 Publication Master en Tecnologies Multimedia Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis Master's thesis
Publisher Place of Publication (up) 08193 Bellaterra, Barcelona (Spain) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ Pov2009 Serial 1625
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Author Joel Barajas; Jaume Garcia; Francesc Carreras; Sandra Pujades; Petia Radeva
Title Angle Images Using Gabor Filters in Cardiac Tagged MRI Type Conference Article
Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 107-114
Keywords Angle Images, Gabor Filters, Harp, Tagged Mri
Abstract Tagged Magnetic Resonance Imaging (MRI) is a non-invasive technique used to examine cardiac deformation in vivo. An Angle Image is a representation of a Tagged MRI which recovers the relative position of the tissue respect to the distorted tags. Thus cardiac deformation can be estimated. This paper describes a new approach to generate Angle Images using a bank of Gabor filters in short axis cardiac Tagged MRI. Our method improves the Angle Images obtained by global techniques, like HARP, with a local frequency analysis. We propose to use the phase response of a combination of a Gabor filters bank, and use it to find a more precise deformation of the left ventricle. We demonstrate the accuracy of our method over HARP by several experimental results.
Address Amsterdam; The Netherlands
Corporate Author Thesis
Publisher IOS Press Place of Publication (up) Amsterdam, The Netherlands Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN 1-58603-560-6 Medium
Area Expedition Conference CAIRD
Notes IAM;MILAB Approved no
Call Number BCNPCL @ bcnpcl @ BGC2005; IAM @ iam Serial 595
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Author Aura Hernandez-Sabate; Debora Gil; Petia Radeva
Title On the usefulness of supervised learning for vessel border detection in IntraVascular Imaging Type Conference Article
Year 2005 Publication Proceeding of the 2005 conference on Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 67-74
Keywords classification; vessel border modelling; IVUS
Abstract IntraVascular UltraSound (IVUS) imaging is a useful tool in diagnosis of cardiac diseases since sequences completely show the morphology of coronary vessels. Vessel borders detection, especially the external adventitia layer, plays a central role in morphological measures and, thus, their segmentation feeds development of medical imaging techniques. Deterministic approaches fail to yield optimal results due to the large amount of IVUS artifacts and vessel borders descriptors. We propose using classification techniques to learn the set of descriptors and parameters that best detect vessel borders. Statistical hypothesis test on the error between automated detections and manually traced borders by 4 experts show that our detections keep within inter-observer variability.
Address
Corporate Author Thesis
Publisher IOS Press Place of Publication (up) Amsterdam, The Netherlands Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ HGR2005c Serial 1549
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Author Enric Marti; Jordi Regincos;Jaime Lopez-Krahe; Juan J.Villanueva
Title Hand line drawing interpretation as three-dimensional objects Type Journal Article
Year 1993 Publication Signal Processing – Intelligent systems for signal and image understanding Abbreviated Journal
Volume 32 Issue 1-2 Pages 91-110
Keywords Line drawing interpretation; line labelling; scene analysis; man-machine interaction; CAD input; line extraction
Abstract In this paper we present a technique to interpret hand line drawings as objects in a three-dimensional space. The object domain considered is based on planar surfaces with straight edges, concretely, on ansextension of Origami world to hidden lines. The line drawing represents the object under orthographic projection and it is sensed using a scanner. Our method is structured in two modules: feature extraction and feature interpretation. In the first one, image processing techniques are applied under certain tolerance margins to detect lines and junctions on the hand line drawing. Feature interpretation module is founded on line labelling techniques using a labelled junction dictionary. A labelling algorithm is here proposed. It uses relaxation techniques to reduce the number of incompatible labels with the junction dictionary so that the convergence of solutions can be accelerated. We formulate some labelling hypotheses tending to eliminate elements in two sets of labelled interpretations. That is, those which are compatible with the dictionary but do not correspond to three-dimensional objects and those which represent objects not very probable to be specified by means of a line drawing. New entities arise on the line drawing as a result of the extension of Origami world. These are defined to enunciate the assumptions of our method as well as to clarify the algorithms proposed. This technique is framed in a project aimed to implement a system to create 3D objects to improve man-machine interaction in CAD systems.
Address
Corporate Author Thesis
Publisher Elsevier North-Holland, Inc. Place of Publication (up) Amsterdam, The Netherlands, The Netherlands Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0165-1684 ISBN Medium
Area Expedition Conference
Notes IAM;ISE; Approved no
Call Number IAM @ iam @ MRL1993 Serial 1611
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Author Ernest Valveny; Enric Marti
Title Application of deformable template matching to symbol recognition in hand-written architectural draw Type Conference Article
Year 1999 Publication Proceedings of the Fifth International Conference on Abbreviated Journal
Volume Issue Pages
Keywords
Abstract We propose to use deformable template matching as a new approach to recognize characters and lineal symbols in hand-written line drawings, instead of traditional methods based on vectorization and feature extraction. Bayesian formulation of the deformable template matching allows combining fidelity to the ideal shape of the symbol with maximum flexibility to get the best fit to the input image. Lineal nature of symbols can be exploited to define a suitable representation of models and the set of deformations to be applied to them. Matching, however, is done over the original binary image to avoid losing relevant features during vectorization. We have applied this method to hand-written architectural drawings and experimental results demonstrate that symbols with high distortions from ideal shape can be accurately identified.
Address
Corporate Author Thesis
Publisher Place of Publication (up) Bangalore (India) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes DAG;IAM; Approved no
Call Number IAM @ iam @ VAM1999a Serial 1657
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Author Albert Andaluz; Francesc Carreras; Debora Gil; Jaume Garcia
Title Una aplicació amigable pel càlcul de indicadors clínics del ventricle esquerre Type Miscellaneous
Year 2010 Publication Forum Biocat 2010 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address Lonja de Mar,Barcelona (Spain)
Corporate Author CVC Thesis
Publisher Biocat Place of Publication (up) Barcelona Editor
Language Catalan Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ ACG2010 Serial 1483
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Author Jaume Garcia; Debora Gil; Francesc Carreras; Sandra Pujades; R.Leta; Xavier Alomar; Guillem Pons-LLados
Title Patrons de Normalitat Regional per la Valoració de la Funció del Ventricle Esquerre Type Conference Article
Year 2008 Publication XX Congrés de la Societat Catalana de Cardiologia Abbreviated Journal
Volume Issue Pages 60
Keywords
Abstract Les malalties cardiovasculars afecten les propietats contràctils de la banda ventricular i provoquen una variació de la funció del Ventricle Esquerre (VE) . Només els indicadors locals (strains, la deformació del teixit) són capaços de detectar anomalies en territoris específics del VE . Patrons de normalitat regionals d’aquests paràmetres serien d’utilitat a l’hora de valorar-ne la funció .
Presentem un Domini Paramètric Normalitzat (DPN) que permet comparar dades de diferents pacients i definir Patrons de Normalitat Regional (PNR)
Address
Corporate Author Thesis
Publisher Place of Publication (up) Barcelona Editor
Language catalan Summary Language catalan Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ GGC2008b Serial 1503
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Author Jaume Garcia; Debora Gil; Francesc Carreras ; Sandra Pujades; R.Leta; Xavier Alomar; Guillem Pons-LLados
Title Un Model 3D del Ventricle Esquerre Integrant Anatomia i Funcionalitat Type Conference Article
Year 2008 Publication XX Congrés de la Societat Catalana de Cardiologia, Actes del Congres Abbreviated Journal
Volume Issue Pages 122
Keywords
Abstract Els canvis en la dinàmica del Ventricle Esquerre (VE) reflecteixen la majoria de malalties cardiovasculars . Els avenços en imatge mèdica han impulsat la recerca en models i simulacions de la dinàmica 3D del VE . La majoria dels models existents sols consideren l’anatomia externa del VE i no permeten una avaluació de l’acoblament electromecànic . Donat que la mecànica d’un muscle depèn de la orientació de les seves fibres, un model realista hauria d’incloure la disposició espacial de la banda ventricular helicoidal (BVH) .
Proposem desenvolupar un model del VE adaptat a cada pacient que integri, per primer cop, l’anatomia de la banda ventricular, l’anatomia externa del VE i la seva funcionalitat, per a una millor determinació del patró d’activació electromecànica
Address
Corporate Author Thesis
Publisher Place of Publication (up) Barcelona Editor
Language catalan Summary Language catalan Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ GGC2008c Serial 1504
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Author Enric Marti; Jaume Rocarias; Ricardo Toledo
Title Caronte: gestión flexible de grupos de alumnos en asignaturas de universidad y actividades sobre estos grupos Type Miscellaneous
Year 2008 Publication Nueva actividad de control, MoodleMoot 2008 Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication (up) Barcelona Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes IAM;RV;ADAS Approved no
Call Number IAM @ iam @ MRT2008b Serial 1618
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