يعرض 1 - 20 نتائج من 651 نتيجة بحث عن '"Data compression (Computer science)"', وقت الاستعلام: 1.24s تنقيح النتائج
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    Dissertation/ Thesis
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    Dissertation/ Thesis
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    Dissertation/ Thesis
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    Conference

    المساهمون: Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques

    وصف الملف: 4 p.; application/pdf

    Relation: https://ieeexplore.ieee.org/document/10207348; info:eu-repo/grantAgreement/EC/HE/101096466/EU/Deep Programmability and Secure Distributed Intelligence for Real-Time End-to-End 6G Networks/DESIRE6G; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114135RB-I00/ES/AI-POWERED INTENT-BASED PACKET AND OPTICAL TRANSPORT NETWORKS AND EDGE AND CLOUD COMPUTING FOR BEYOND 5G/; El Sayed, A. [et al.]. Comparison of statistical and machine learning-based approaches for telemetry data size reduction. A: International Conference on Transparent Optical Networks. "ICTON 2023: 23rd International Conference on Transparent Optical Networks: 2-6 July 2023, Bucharest, Romania". Institute of Electrical and Electronics Engineers (IEEE), 2023. ISBN 979-8-3503-0303-2. DOI 10.1109/ICTON59386.2023.10207348.; 979-8-3503-0303-2; http://hdl.handle.net/2117/397620

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    Academic Journal

    المساهمون: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

    وصف الملف: 36 p.; application/pdf

    Relation: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278346; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105660RB-C21/ES/JERARQUIA DE MEMORIA, GESTION DE TAREAS Y OPTIMIZACION DE APLICACIONES/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-107255GB-C22/ES/UPC-COMPUTACION DE ALTAS PRESTACIONES VIII/; Escuín, C. [et al.]. L2C2: Last-level compressed-contents non-volatile cache and a procedure to forecast performance and lifetime. "PloS one", 7 Febrer 2023, vol. 18, núm. 2, article e0278346, p. 1-36.; http://hdl.handle.net/2117/386455

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    Conference

    المساهمون: Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions

    وصف الملف: 5 p.; application/pdf

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    Academic Journal

    المساهمون: Universitat Politècnica de Catalunya. Doctorat en Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions

    وصف الملف: 21 p.; application/pdf

    Relation: https://www.mdpi.com/2072-4292/14/9/2063; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095076-B-C21/ES/LOS DATOS DE GAIA PARA LAS PROXIMAS DECADAS II/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114322RB-I00/ES/IMPACTOS DE LARGO ALCANCE DE LAS CASCADAS DE AGUA DENSA EN EL OCEANO ATLANTICO NORTE Y EL MAR MEDITERRANEO (FAR-DWO)/; info:eu-repo/grantAgreement/EC/H2020/658358/EU/Seabed Imprint of Dense Shelf Water Cascading/SIDEW; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-105717RB-C22/ES/METODOS ROBUSTOS PARA INFERENCIA ESTADISTICA, INTEGRIDAD DE DATOS Y GESTION DE INTERFERENCIA - 2/; Martí, A. [et al.]. Compression of multibeam echosounders bathymetry and water column data. "Remote sensing", 25 Abril 2022, vol. 14, núm. 9, article 2063, p. 1-21.; http://hdl.handle.net/2117/368205

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    Dissertation/ Thesis
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    Conference

    المساهمون: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. Doctorat en Enginyeria Electrònica, Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. GCO - Grup de Comunicacions Òptiques

    وصف الملف: 4 p.; application/pdf

    Relation: https://ieeexplore.ieee.org/document/9606175; info:eu-repo/grantAgreement/EC/H2020/813144/EU/REAL-time monitoring and mitigation of nonlinear effects in optical NETworks/REAL-NET; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TEC2017-90097-R/ES/COGNITIVE 5G APPLICATION-AWARE OPTICAL METRO NETWORKS INTEGRATING MONITORING, DATA ANALYTICS AND OPTIMIZATION/; https://doi.org/10.34810/data146; Ruiz, M. [et al.]. An autoencoder-based solution for IQ constellation analysis. A: European Conference on Optical Communication. "European Conference on Optical Communication, ECOC 2021: Bordeaux, France, September 13-16, 2021". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 1-4. ISBN 978-1-6654-3868-1. DOI 10.1109/ECOC52684.2021.9606175.; http://hdl.handle.net/2117/361753

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    Academic Journal

    المساهمون: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors

    وصف الملف: application/pdf

    Relation: https://www.sciencedirect.com/science/article/abs/pii/S0167739X24002553; Cappello, F. [et al.]. Multifacets of lossy compression for scientific data in the Joint-Laboratory of Extreme Scale Computing. "Future generation computer systems", 13 Juny 2024.; http://hdl.handle.net/2117/412665

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    Academic Journal

    المساهمون: Universitat Politècnica de Catalunya. Doctorat en Arquitectura de Computadors, Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. IMP - Information Modeling and Processing

    وصف الملف: 20 p.; application/pdf

    Relation: https://link.springer.com/article/10.1007%2Fs11042-021-10720-7; info:eu-repo/grantAgreement/MINECO//TEC2015-67774-C2-1-R/ES/SECURE GENOMIC INFORMATION COMPRESSION/; info:eu-repo/grantAgreement/AGAUR/2017 SGR 1749; Naro, D.; Delgado, J.; Llorente, S. Side channel attack on a partially encrypted MPEG-G file. "Multimedia tools and applications", Maig 2021, vol. 80, núm. 3, p. 20599-20618.; http://hdl.handle.net/2117/342757

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    Dissertation/ Thesis
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    Report

    المساهمون: Carlson, Jeffrey

    وصف الملف: Medium: ED; Size: 54 p.

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    Dissertation/ Thesis

    المؤلفون: Araujo, Isis Ferreira

    المساهمون: Oliveira, Rafael Alves Paes de, Souza, Francisco Carlos Monteiro, Lopes, Yuri Kaszubowski

    وصف الملف: application/pdf

    Relation: ARAUJO, Isis Ferreira. Cultura orientada por dados e análise de negócios no setor público: uma abordagem para aprimorar a tomada de decisões. 2023. Monografia (Especialização em Tecnologia Python para Negócios) - Universidade Tecnológica Federal do Paraná, Dois Vizinhos, 2023.; http://repositorio.utfpr.edu.br/jspui/handle/1/31599

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    Academic Journal

    المصدر: https://www.sciencedirect.com/science/article/pii/S0262885617301245 ; reponame:Repositorio Institucional UAO.

    Time: Universidad Autónoma de Occidente. Calle 25 115-85. Km 2 vía Cali-Jamundí

    وصف الملف: application/pdf; 12 páginas

    Relation: 124; 113; 69; Villota, J. C. P., da Silva, F. L., de Souza Jacomini, R., & Costa, A. H. R. (2018). Pairwise registration in indoor environments using adaptive combination of 2D and 3D cues. Image and Vision Computing, 69, 113-124; Image and Vision Computing, volumen 69, páginas 113-124, (january, 2018); [1] Z. Xie, S. Xu, X. Li, A high-accuracy method for fine registration of overlapping point clouds, Image Vis. Comput. 28 (4) (2010) 563–570.; [2] P. Henry, M. Krainin, E. Herbst, X. Ren, D. Fox, RGB-D mapping: using Kinect-style depth cameras for dense 3D modeling of indoor environments, Int. J. Robot. Res. 31 (5) (2012) 647–663.; [3] S. Li, A. Calway, RGBD relocalisation using pairwise geometry and concise key point sets, IEEE Int. Conf. Robot. Autom. (ICRA) (2015) 6374–6379.; [4] B.C. Russell, J. Sivic, W.T. Freeman, A. Zisserman, A.a. Efros, Segmenting scenes by matching image composites, Adv. Neural Inf. Proces. Syst. (NIPS) (2009) 1–9.; [5] S. Gupta, P. Arbelaez, R. Girshick, J. Malik, Indoor scene understanding with RGB-D images: bottom-up segmentation, object detection and semantic segmentation, Int. J. Comput. Vis. 112 (2) (2015) 133–149.; [6] T. Shao, W. Xu, K. Zhou, J. Wang, D. Li, B. Guo, An interactive approach to semantic modeling of indoor scenes with an RGBD camera, ACM Trans. Graph 31 (6). (2012)136:1–136:11.; [7] A. Geiger, C. Wang, Joint 3D object and layout inference from a single RGB-D image, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9358, 2015. pp. 183–195.; [8] M. Firman, D. Thomas, S. Julier, A. sugimoto, Learning to discover objects in RGB-D images using correlation clustering, IEEE International Conference on Intelligent Robots and Systems (IROS), 2013. pp. 1107–1112.; [9] E. Bylow, J. Sturm, C. Kerl, F. Kahl, D. Cremers, Real-time camera tracking and 3D reconstruction using signed distance functions, Robotics: Science and Systems Conference (RSS), 2013.; [10] T. Tykkälä, A.I. Comport, J.K. Kämäräinen, H. Hartikainen, Live RGB-D camera tracking for television production studios, J. Vis. Commun. Image Represent. 25 (1) (2014) 207–217.; [11] V. Morell-Gimenez, M. Saval-Calvo, J. Azorin-Lopez, J. Garcia-Rodriguez, M. Cazola, S. Orts-Escolano, A. Fuster-Guillo, A comparative study of registration methods for RGB-D video of static scenes, Sensors 14 (1) (2014) 8547–8576.; [12] D.G. Lowe, Distinctive image features from scale-invariant keypoints, Int. J. Comput. Vis. 60 (2) (2004) 91–110.; [13] Y. Díez, F. Roure, X. Llado, J. Salvi, A qualitative review on 3D coarse registration methods, ACM Comput. Surv. 47 (3) (2015) 1–36.; [14] M. Fischler, R.C. Bolles, Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Commun. ACM 24 (6) (1981) 381–395.; [15] F. Endres, J. Hess, N. Engelhard, J. Sturm, D. Cremers, W. Burgard, An evaluation of the RGB-D SLAM system, IEEE International Conference on Robotics and Automation (ICRA), 2012. pp. 1691–1696.; [16] D. Holz, A.E. Ichim, F. Tombari, R.B. Rusu, S. Behnke, Registration with the point cloud library: a modular framework for aligning in 3-D, IEEE Robot. Autom. Mag. 22 (4) (2015) 110–124.; [17] S.M. Prakhya, U. Qayyum, Sparse depth odometry: 3D keypoint based pose estimation from dense depth data, IEEE International Conference on Robotics and Automation (ICRA), 2015. pp. 4216–4223.; [18] C.-C. Wang, C. Thorpe, S. Thrun, M. Hebert, H. Durrant-Whyte, Simultaneous localization, mapping and moving object tracking, Int. J. Robot. Res. 26 (9) (2007) 889–916. Sage Publications.; [19] A. Aldoma, F. Tombari, L.D. Stefano, M. Vincze, A global hypothesis verification framework for 3D object recognition in clutter, IEEE Trans. Pattern Anal. Mach. Learn 38 (7) (2016) 1383–1396.; [20] J. Xie, Y.-F. Hsu, R.S. Feris, M.-T. Sun, Fine registration of 3D point clouds fusing structural and photometric information using an RGB-D camera, J. Vis. Commun. Image Represent. 32 (1) (2015) 194–204.; [21] P.J. Besl, N.D. McKay, A method for registration of 3-D shapes, IEEE Trans. Pattern Anal. Mach. Learn 14 (2) (1992) 239–256.; [22] H. Kim, A. Hilton, Influence of colour and feature geometry on multi-modal 3D point clouds data registration, 2nd International Conference on 3D Vision, 1, 2014. pp. 202–209.; [23] J.C.P. Villota, A.H.R. Costa, Aligning RGB-D point clouds through adaptive integration of color and depth cues, 12th Latin American Robotics Symposium (LARS), 2015. pp. 309–314.; [24] D.G. Lowe, Object recognition from local scale-invariant features, 7th IEEE International Conference on Computer Vision (ICCV), 2, 1999. pp. 1150–1157.; [25] E. Rosten, R. Porter, T. Drummond, Faster and better: a machine learning approach to corner detection, IEEE Trans. Pattern Anal. Mach. Intell. 32 (1) (2010) 105–119.; [26] M. Calonder, V. Lepetit, P. Fua, Keypoint signatures for fast learning and recognition, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5302, 2008. pp. 58–71. LNCS.; [27] E. Rublee, V. Rabaud, K. Konolige, G. Bradski, ORB: an efficient alternative to SIFT or SURF, IEEE International Conference on Computer Vision (ICCV), 2011. pp. 2564–2571.; [28] H. Bay, T. Tuytelaars, L.V.a.n. Gool, SURF: speeded up robust features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3951, 2006. pp. 404–417. lNCS.; [29] S. Filipe, L.A. Alexandre, A comparative evaluation of 3D keypoint detectors in a RGB-D object dataset, IEEE International Conference on Computer Vision Theory and Applications (VISAPP), 2014. pp. 476–483.; [30] C. Harris, M. Stephens, A combined corner and edge detector, Alvey Vision Conference, 1988. pp. 147–151.; [31] C. Tomasi, T. Kanade, Detection and tracking of point features, Technical Report CMU-CS-91-132, School of Computer Science, Carnegie Mellon University. 1991. pp. 1–22.; [32] A. Flint, A. Dick, A. Van Den Hengel, Thrift: local 3D structure recognition, 9th Biennial Conference of the Australian Pattern Recognition Society, Digital Image Computing Techniques and Applications (DICTA), 2007. pp. 182–188.; [33] S. Smith, J. Brady, SUSANA: a new approach to low level image processing, Int. J. Comput. Vis. 23 (1) (1997) 45–78.; [34] Z. Yu, Intrinsic shape signatures: a shape descriptor for 3D object recognition, IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops. 2009, pp. 689–696.; [35] M. Desbrun, M. Meyer, P. Schröder, A.H. Barr, Implicit fairing of irregular meses using diffusion and curvature flow, 26th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 1999. pp. 317–324.; [36] R.B. Rusu, S. Cousins, 3D is here: point cloud library, IEEE International Conference on Robotics and Automation (ICRA), 2011. pp. 1–4.; [37] B. Steder, R. Rusu, K. Konolige, W. Burgard, NARF: 3D range image features for object recognition, Workshop on Defining and Solving Realistic Perception Problems in Personal Robotics at the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems (IROS), 2010.; [38] T. Fiolka, J. Stuckler, D.A. Klein, D. Schulz, S. Behnke, SURE: surface entropy for distinctive 3D features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7463, 2012. pp. 74–93. LNAI.; [39] S. Salti, A. Petrelli, F. Tombari, L.D. Stefano, On the affinity between 3D detectors and descriptors, Second Joint 3DIM/3DPVT Conference: 3D Imaging, Modeling, Processing, Visualization & Transmission, 1, 2012. pp. 425–4313.; [40] R. Hänsch, T. Weber, O. Hellwich, Comparison of 3D interest point detectors and descriptors for point cloud fusion, ISPRS Annals of Photogrammetry, Remote. Sens. Spat. Inf. Sci. (2014) 57–64. II-3 (September).; [41] Y. Guo, M. Bennamoun, F. Sohel, M. Lu, J. Wan, N.M. Kwok, A comprehensive performance evaluation of 3D local feature descriptors, Int. J. Comput. Vis. 116 (1) (2016) 66–89.; [42] R.B. Rusu, N. Blodow, M. Beetz, Fast point feature histograms (FPFH) for 3D registration, IEEE International Conference on Robotics and Automation (ICRA), 2009. pp. 3212–3217.; [43] S. Salti, F. Tombari, L. Di Stefano, SHOT: unique signatures of histograms for surface and texture description, Comput. Vis. Image Underst. 125 (2014) 251–264.; [44] M. Muja, D.G. Lowe, Scalable nearest neighbor algorithms for high dimensional data, IEEE Trans. Pattern Anal. Mach. Intell. 36 (11) (2014) 2227–2240.; [45] T. Ojala, M. Pietikainen, D. Harwood, Performance evaluation of texture measures with classification based on Kullback discrimination of distributions, 12th International Conference on Pattern Recognition (ICPR), 1, 1994. pp. 582–585.; [46] S. Chun, C. Lee, S. Lee, Facial expression recognition using extended local binary patterns of 3D curvature, Multimedia and Ubiquitous Engineering, 2013. pp. 1005–1012.; [47] C. Cortes, V. Vapnik, Support-vector networks, Mach. Learn. 20 (3) (1995) 273–297.; [48] J. Sturm, N. Engelhard, F. Endres, W. Burgard, D. Cremers, A benchmark for the evaluation of RGB-D SLAM systems, IEEE International Conference on Intelligent Robots and Systems (IROS), 2012. pp. 573–580.; [49] J. Russell, P. Norvig, Artificial Intelligence: A Modern Approach, Third ed., Pearson Education, Inc, 2010.; http://hdl.handle.net/10614/11388; https://doi.org/10.1016/j.imavis.2017.08.008

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    Report

    المساهمون: Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors, Universitat Politècnica de Catalunya. IMP - Information Modeling and Processing

    وصف الملف: 1 p.; application/pdf

    Relation: https://f1000research.com/posters/8-1071; info:eu-repo/grantAgreement/MINECO//TEC2015-67774-C2-1-R/ES/SECURE GENOMIC INFORMATION COMPRESSION/; Repchevsky, D. [et al.]. "jmpegg 1.0 – the pure java implementation of the MPEG-G ISO/IEC 23092 standard". 2019.; http://hdl.handle.net/2117/168998

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