Academic literature on the topic 'VoxSRC'

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Journal articles on the topic "VoxSRC"

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Teichrieb, Veronica, Francisco Simões, Lucas Figueiredo, João Paulo Lima, João Marcelo Teixeira, Rafael Roberto, Alana Da Gama, Thiago Chaves, Arlindo Gomes, and Maria de Lourdes Euzébio. "Voxar Labs." Comunicações em Informática 4, no. 2 (November 9, 2020): 43–46. http://dx.doi.org/10.22478/ufpb.2595-0622.2020v4n2.54447.

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Voxar Labs is a research group focused in augmenting experiences through research, innovation and collaboration with academia and industry. It develops cutting-edge multi-disciplinary research in the large area of Spatial Computing, tackling the inner areas of Extended Reality, Computer Vision and Natural Interaction. The laboratory aims to create impact through R&D&I, technology transfer, scientific publications, patents and human-resources formation. It is one of the most productive Augmented Reality research groups in the Latin America, also being recognized with seven best papers and ten first-place competitions’ prizes over the nine years of its existence. Voxar Labs is part of the Informatics Center of the Federal University of Pernambuco, located in Recife – Pernambuco, Brazil.
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Teichrieb, Veronica, and The VOXAR Labs Team. "VOXAR Labs - augmenting experiences for a better life." Journal on Interactive Systems 2, no. 2 (November 16, 2011): 1. http://dx.doi.org/10.5753/jis.2011.589.

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The VOXAR Labs is a research group with the mission of developing people by augmenting experiences. It develops and transfers technology related to visualization, tracking and natural interaction techniques focusing augmented reality in multi-disciplinary application domains. The laboratory has several ongoing projects including an international cooperation, projects with the industry, involving energy and military ones, as well as research and academic projects. VOXAR Labs is part of the Informatics Center of the Federal University of Pernambuco, located in Recife – Pernambuco, Brazil.
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Green, Tim. "Voxer: a Digital Messaging Tool." TechTrends 60, no. 3 (March 28, 2016): 299–302. http://dx.doi.org/10.1007/s11528-016-0062-3.

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Pitot, P. "The Voxar project (parallel ray-tracing)." IEEE Computer Graphics and Applications 13, no. 1 (January 1993): 27–33. http://dx.doi.org/10.1109/38.180114.

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Karambakhsh, Ahmad, Bin Sheng, Ping Li, Po Yang, Younhyun Jung, and David Dagan Feng. "VoxRec: Hybrid Convolutional Neural Network for Active 3D Object Recognition." IEEE Access 8 (2020): 70969–80. http://dx.doi.org/10.1109/access.2020.2987177.

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Pitot, P., B. Moisan, Y. Duthen, and R. Caubet. "A transputer based implementation of the VOXAR project." Microprocessing and Microprogramming 30, no. 1-5 (August 1990): 347–53. http://dx.doi.org/10.1016/0165-6074(90)90265-b.

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Makoś-Chełstowska, Patrycja, Edyta Słupek, and Jacek Gębicki. "Deep eutectic solvent-based green absorbents for the effective removal of volatile organochlorine compounds from biogas." Green Chemistry 23, no. 13 (2021): 4814–27. http://dx.doi.org/10.1039/d1gc01735g.

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Yang, Weimin, Yubo Tao, and Hai Lin. "Voxer—a platform for creating, customizing, and sharing scientific visualizations." Journal of Visualization 22, no. 6 (September 3, 2019): 1161–76. http://dx.doi.org/10.1007/s12650-019-00595-0.

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van der Heyden, Brent, Lotte E. J. R. Schyns, Mark Podesta, Ana Vaniqui, Isabel P. Almeida, Guillaume Landry, and Frank Verhaegen. "VOXSI: A voxelized single- and dual-energy CT scenario generator for quantitative imaging." Physics and Imaging in Radiation Oncology 6 (April 2018): 47–52. http://dx.doi.org/10.1016/j.phro.2018.05.004.

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Carpenter, Jeffrey Paul, and Tim D. Green. "Mobile instant messaging for professional learning: Educators' perspectives on and uses of Voxer." Teaching and Teacher Education 68 (November 2017): 53–67. http://dx.doi.org/10.1016/j.tate.2017.08.008.

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Dissertations / Theses on the topic "VoxSRC"

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Lukáč, Peter. "Verifikace osob podle hlasu bez extrakce příznaků." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445531.

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Verifikácia osôb je oblasť, ktorá sa stále modernizuje, zlepšuje a snaží sa vyhovieť požiadavkám, ktoré sa na ňu kladú vo oblastiach využitia ako sú autorizačné systmémy, forenzné analýzy, atď. Vylepšenia sa uskutočňujú vďaka pokrom v hlbokom učení, tvorením nových trénovacích a testovacích dátovych sad a rôznych súťaží vo verifikácií osôb a workshopov. V tejto práci preskúmame modely pre verifikáciu osôb bez extrakcie príznakov. Používanie nespracovaných zvukových stôp ako vstupy modelov zjednodušuje spracovávanie vstpu a teda znižujú sa výpočetné a pamäťové požiadavky a redukuje sa počet hyperparametrov potrebných pre tvorbu príznakov z nahrávok, ktoré ovplivňujú výsledky. Momentálne modely bez extrakcie príznakov nedosahujú výsledky modelov s extrakciou príznakov. Na základných modeloch budeme experimentovať s modernými technikamy a budeme sa snažiť zlepšiť presnosť modelov. Experimenty s modernými technikamy značne zlepšili výsledky základných modelov ale stále sme nedosiahli výsledky vylepšeného modelu s extrakciou príznakov. Zlepšenie je ale dostatočné nato aby sme vytovrili fúziu so s týmto modelom. Záverom diskutujeme dosiahnuté výsledky a navrhujeme zlepšenia na základe týchto výsledkov.
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Cipres, de Cacqueray Pascale. "La génération d'objets texturés : application à la machine VOXAR." Toulouse 3, 1990. http://www.theses.fr/1990TOU30084.

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Pour obtenir des images realistes en synthese d'images, il faut prendre en compte la texture des objets, leur representation visuelle. Les etudes comparatives des differents modeles de texture, des methodes de projection ou pavage d'un motif de texture sur les objets et des techniques de filtrage de l'image pour combattre l'aliassage ont abouti a la realisation de modeles de textures solides, plus adaptes a la geometrie tridimensionnelle des objets. Nous presentons une solution optimale dans le cas de l'animation de scenes et des applications sur les machines a parallelisme objet en integrant l'information de texture lors de l'etape de modelisation de l'objet. L'objet est alors discretise et constitue par un ensemble de particules de matiere, ou atomes dans le sens de la definition propre de la texture. Ainsi, les temps de calcul entre une image sans texture et une image dont les objets sont textures sont identiques. L'implementation realisee sur la machine multiprocesseurs voxar, orientee objet et dediee a l'algorithme de lancer de rayons valide cette methode
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Pitot, Paul. "Conception et réalisation d'une machine parallèle dédiée aux images de synthèse réalistes : la machine Voxar." Toulouse 3, 1991. http://www.theses.fr/1991TOU30011.

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Utile à la conception d'objets, interface de haut niveau entre la machine et l'homme, l'image de synthèse nous permettra demain d'utiliser pleinement notre vue. Le réalisme d'une image dépend de la complexité du modèle d'éclairage utilisé. Le lancer de rayons, utilisé dans les modèles les plus réalistes, est encore trop couteux pour les machines actuellement disponibles. Les méthodes de subdivision spatiales permettent de réduire fortement la complexité initiale du lancer de rayons, mais elles apparaissent inadaptées aux super-calculateurs commerciaux. C'est pourquoi de nombreuses recherches ont visé à leur implantation sur des réseaux multiprocesseurs. L'ambition du projet Voxar est d'exploiter le parallélisme naturel d'une scène dont les éléments de matière échangent des sollicitations (rayons) via l'espace. La scène, découpée en voxels, est enroulée autour d'un réseau de processeurs connectés en tore de dimension 3. Cette association entre l'espace et les processeurs répartit les données en conservant les propriétés topologiques de l'espace à travers les connexions du réseau. Une maquette composée de 36 transputers a été réalisée ; des scènes complexes peuvent être chargées, animées et visualisées par lancer de rayon. Le rendement du réseau est compris entre 25 et 76 pour cents selon la scène et l'image calculée. Les meilleures performances apparaissent lorsque les scènes et les images calculées sont complexes. C'est la répartition des données, qui n'est pas toujours bonne, qui semble surtout limiter les performances du modèle
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Gaildrat, Véronique. "Contribution à l'étude et à la conception d'une machine parallèle pour la production rapide d'images de synthèse la machine VOXAR : conception de l'application synthèse d'images réalistes /." Grenoble 2 : ANRT, 1988. http://catalogue.bnf.fr/ark:/12148/cb376137398.

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Gaildrat, Véronique. "Contribution a l'etude et a la conception d'une machine parallele pour la production rapide d'images de synthese : la machine voxar, conception de l'application synthese d'images realistes." Toulouse 3, 1988. http://www.theses.fr/1988TOU30199.

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L'objectif est de reduire les temps d'obtention d'images de synthese realistes par la technique du lancer de rayon. Un logiciel de synthese d'images, applique a des objets modelises par composition de primitives geometriques, est propose. Afin d'exploiter le parallelisme d'ecran et la coherence spatiale d'une scene, une architecture parallele a ete introduite
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Book chapters on the topic "VoxSRC"

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Caubet, R., Y. Duthen, and V. Gaildrat. "VOXAR: A Tridimensional Architecture for Fast Realistic Image Synthesis." In New Trends in Computer Graphics, 135–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/978-3-642-83492-9_13.

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Carpenter, Jeffrey P., and Tim D. Green. "Self-directed Professional Learning and Educator Self-Efficacy: The Case of Voxer." In Self-Efficacy in Instructional Technology Contexts, 163–81. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99858-9_10.

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Shi, Zenglin, Guodong Zeng, Le Zhang, Xiahai Zhuang, Lei Li, Guang Yang, and Guoyan Zheng. "Bayesian VoxDRN: A Probabilistic Deep Voxelwise Dilated Residual Network for Whole Heart Segmentation from 3D MR Images." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2018, 569–77. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00937-3_65.

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Conference papers on the topic "VoxSRC"

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Garcia-Romero, Daniel, Alan McCree, David Snyder, and Gregory Sell. "Jhu-HLTCOE System for the Voxsrc Speaker Recognition Challenge." In ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2020. http://dx.doi.org/10.1109/icassp40776.2020.9053209.

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Kwon, Yoohwan, Hee-Soo Heo, Bong-Jin Lee, and Joon Son Chung. "The ins and outs of speaker recognition: lessons from VoxSRC 2020." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413948.

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Thienpondt, Jenthe, Brecht Desplanques, and Kris Demuynck. "The Idlab Voxsrc-20 Submission: Large Margin Fine-Tuning and Quality-Aware Score Calibration in DNN Based Speaker Verification." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9414600.

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Xie, Yusheng, Daniel Honbo, Alok Choudhary, Kunpeng Zhang, Yu Cheng, and Ankit Agrawal. "VOXSUP." In the 18th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2339530.2339779.

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Teichrieb, Veronica, Francisco Simões, Lucas Figueiredo, João Paulo Lima, João Marcelo Teixeira, Rafael Roberto, Alana Da Gama, Thiago Chaves, Arlindo Gomes, and Maria Euzébio. "Voxar Labs." In Anais Estendidos do Simpósio de Realidade Virtual e Aumentada. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/svr_estendido.2020.12974.

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Voxar Labs is a research group focused in augmenting experiences through research, innovation and collaboration with academia and industry. It develops cutting-edge multi-disciplinary research in the large area of Spatial Computing, tackling the inner areas of Extended Reality, Computer Vision and Natural Interaction. The laboratory aims to create impact through R&D&I, technology transfer, scientific publications, patents and human-resources formation. It is one of the most productive Augmented Reality research groups in the Latin America, also being recognized with seven best papers and ten first-place competitions’ prizes over the nine years of its existence. Voxar Labs is part of the Informatics Center of the Federal University of Pernambuco, located in Recife – Pernambuco, Brazil.
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Fadzli, Fazliaty Edora, and Ajune Wanis Ismail. "VoxAR: 3D Modelling Editor Using Real Hands Gesture for Augmented Reality." In 2019 IEEE 7th Conference on Systems, Process and Control (ICSPC). IEEE, 2019. http://dx.doi.org/10.1109/icspc47137.2019.9067992.

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Roberto, Rafael A., Manoela M. O. da Silva, Daniel Q. Freitas, Yvonne C. C. A. Lima, Vinicius E. M. Silva, Cristiano C. Araujo, Joao Marcelo X. N. Teixeira, and Veronica Teichrieb. "Voxar puzzle motion: an innovative ar application proposed using design techniques." In 2016 IEEE Virtual Reality Workshop on K-12 Embodied Learning through Virtual & Augmented Reality (KELVAR). IEEE, 2016. http://dx.doi.org/10.1109/kelvar.2016.7563676.

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Silva, Vinicius Emanuel, Caio Lins, Andre Silva, Rafael Roberto, Cristiano Araujo, and Veronica Teichrieb. "Voxar Puzzle: An Innovative Hardware/Software Computer Vision Game for Children Development." In 2015 XVII Symposium on Virtual and Augmented Reality (SVR). IEEE, 2015. http://dx.doi.org/10.1109/svr.2015.29.

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