Готові списки джерел за темами / PROCESSING FRAMEWORK

Добірка наукової літератури з теми "PROCESSING FRAMEWORK"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "PROCESSING FRAMEWORK"

Soller, Dominik, Thomas Jaumann, Gerd Kilian, Jörg Robert, and Albert Heuberger. "DFC++ Processing Framework Concept." Journal of Signal Processing Systems 89, no. 1 (August 18, 2016): 181–90. http://dx.doi.org/10.1007/s11265-016-1174-x.

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Patel, Karan, Yash Sakaria, and Chetashri Bhadane. "Real Time Data Processing Framework." International Journal of Data Mining & Knowledge Management Process 5, no. 5 (September 30, 2015): 49–63. http://dx.doi.org/10.5121/ijdkp.2015.5504.

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Zhuo, Youwei, Jingji Chen, Gengyu Rao, Qinyi Luo, Yanzhi Wang, Hailong Yang, Depei Qian, and Xuehai Qian. "Distributed Graph Processing System and Processing-in-memory Architecture with Precise Loop-carried Dependency Guarantee." ACM Transactions on Computer Systems 37, no. 1-4 (June 2021): 1–37. http://dx.doi.org/10.1145/3453681.

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To hide the complexity of the underlying system, graph processing frameworks ask programmers to specify graph computations in user-defined functions (UDFs) of graph-oriented programming model. Due to the nature of distributed execution, current frameworks cannot precisely enforce the semantics of UDFs, leading to unnecessary computation and communication. It exemplifies a gap between programming model and runtime execution. This article proposes novel graph processing frameworks for distributed system and Processing-in-memory (PIM) architecture that precisely enforces loop-carried dependency; i.e., when a condition is satisfied by a neighbor, all following neighbors can be skipped. Our approach instruments the UDFs to express the loop-carried dependency, then the distributed execution framework enforces the precise semantics by performing dependency propagation dynamically. Enforcing loop-carried dependency requires the sequential processing of the neighbors of each vertex distributed in different nodes. We propose to circulant scheduling in the framework to allow different nodes to process disjoint sets of edges/vertices in parallel while satisfying the sequential requirement. The technique achieves an excellent trade-off between precise semantics and parallelism—the benefits of eliminating unnecessary computation and communication offset the reduced parallelism. We implement a new distributed graph processing framework SympleGraph, and two variants of runtime systems— GraphS and GraphSR —for PIM-based graph processing architecture, which significantly outperform the state-of-the-art.

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Ramamoorthi, Ravi, and Pat Hanrahan. "A signal-processing framework for reflection." ACM Transactions on Graphics 23, no. 4 (October 2004): 1004–42. http://dx.doi.org/10.1145/1027411.1027416.

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Sivaswamy, Jayanthi. "Framework for practical hexagonal-image processing." Journal of Electronic Imaging 11, no. 1 (January 1, 2002): 104. http://dx.doi.org/10.1117/1.1426078.

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Ye, Yinghao, Meilin Wang, Shuhong Yao, Jarvis N. Jiang, and Qing Liu. "Big data processing framework for manufacturing." Procedia CIRP 83 (2019): 661–64. http://dx.doi.org/10.1016/j.procir.2019.04.109.

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Chan, Daniel K. C., and Philip W. Trinder. "A processing framework for object comprehensions." Information and Software Technology 39, no. 9 (January 1997): 641–51. http://dx.doi.org/10.1016/s0950-5849(97)00014-1.

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Soto, David, Usman Ayub Sheikh, and Clive R. Rosenthal. "A Novel Framework for Unconscious Processing." Trends in Cognitive Sciences 23, no. 5 (May 2019): 372–76. http://dx.doi.org/10.1016/j.tics.2019.03.002.

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Haochen Zou, Haochen Zou, Dejian Wang Haochen Zou, and Yang Xiao Dejian Wang. "Annolog: A Query Processing Framework for Modelling and Reasoning with Annotated Data." 電腦學刊 34, no. 2 (April 2023): 081–97. http://dx.doi.org/10.53106/199115992023043402007.

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<p>Data annotation is the categorization and labelling of data for applications, such as machine learning, artificial intelligence, and data integration. The categorization and labelling are done to achieve a specific use case in relation to solving problems. Existing data annotation systems and modules face imperfections such as knowledge and annotation not being formally integrated, narrow application range, and difficulty to apply on existing database management applications. To analyze and process annotated data, obtain the relationship between different annotations, and capture metainformation in data provenance and probabilistic databases, in this paper, we design a back-end query processing framework as a supplementary interface for the database management system to extend operation to datasets and boost efficiency. The framework utilizes Java language and the MVC model for development to achieve lightweight, cross-platform, and high adaptability identities. The contribution of this paper is mainly reflected in two aspects. The first contribution is to implement query processing, provenance semiring, and semiring homomorphism over annotated data. The second contribution is to combine query processing and provenance with SQL statements in order to enable the database manager to invoke operations to annotation.</p> <p> </p>

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POWELL, MARK W., and DMITRY GOLDGOF. "SOFTWARE TOOLKIT FOR TEACHING IMAGE PROCESSING." International Journal of Pattern Recognition and Artificial Intelligence 15, no. 05 (August 2001): 833–44. http://dx.doi.org/10.1142/s0218001401001180.

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We introduce a software framework called the Java Vision Toolkit (JVT) for teaching image processing and computer vision. The toolkit provides over 50 image operations and presents them to the user in a GUI that can render grayscale, color and 3D range images. The software is written in Java, enabling it to be integrated into HTML documents and interactive course materials. The framework is designed for extensibility using a source code template that supports the implementation of any new operation with a minimal amount of supporting code. For students, this framework encapsulates the GUI, file I/O and other trivial programming details and allows them the maximum amount of time to spend on understanding computer vision. We compare the JVT with other computer vision software frameworks that are used for teaching and research. We also discuss the use of the JVT in an undergraduate image processing course at the University of South Florida.

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Дисертації з теми "PROCESSING FRAMEWORK"

Childress, Lawrence. "The Loss-Processing Framework." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/etd/3896.

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The circumstances of responding to loss due to human death are among the most stressful experiences encountered in life. Although grief’s symptoms are typically considered essential to their gradual diminishment, possible negative impacts of complications related to grief are also well known, and have been associated with detriments to mental and physical health. Grief, however, can also generate transformative positive change. Thus, albeit ineludible, responding to loss is not uniformly experienced, expressed, or understood. It is also culturally-shaped, making attempts to define “normal” grief, as well as to label some grief “abnormal”—and to medicalize it—possibly problematic. Bereavement (the situation surrounding a death) and mourning (the publicly expressed response to loss due to death) are changing. Some of these changes (e.g., the increase in hospice care settings prior to deaths, and alterations in the ritual responses following all deaths—irrespective of their context) may have important implications for avoiding grief’s possible complications and for promoting its potential benefits. An improved alignment of grief theory, research, and practice is warranted; but theories of grief are diverse, and historically have not been empirically well-supported. This research articulates a new grief model, the loss-processing framework, featuring three dimensional components (perception, orientation, and direction). As a first step toward validation of the framework, also included is an empirical study examining retrospective descriptive reports of adult loss response relating to the first of these three dimensions (perception). As an interpretive, translational approach to understanding grief, the loss-processing framework may serve to positively impact grieving, health, and life quality.

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Pluskal, Jan. "Framework for Captured Network Communication Processing." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2014. http://www.nusl.cz/ntk/nusl-413326.

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Práce pojednává o možnostech získávání dat a jejich analýzy ze zachycené síťové komunikace. Jsou zhodnoceny možnosti aktuálně dostupných řešení jednotlivých nástrojů i celých prostředí pro síťovou forenzní analýzu. Provedením analýzy těchto nástrojů byly zjištěny nedostatky, pro které není možná integrace již hotových řešení pro záměry projektu SEC6NET, a dále byly stanoveny cíle, které navržené řešení musí splňovat. Na základě cílů a znalostí z předchozích prototypů řešení byla provedena dekompozice problému na jednotlivé funkčně související bloky, které byly implementovány jako nezávislé moduly schopny spolupráce. Správná funkcionalita je po každé změně v implementaci testována pomocí sad Unit testů, které pokrývají majoritní část kódu. Před zahájením samotného vývoje bylo nutné zhodnotit aktuální situaci v komerčních i open-source sférách řešení. Srovnání nástrojů používaných pro forenzní síťovou analýzu nám dalo jasnou představu, na kterou část trhu chce naše řešení směřovat a jaká funkčnost je v jednotlivých nástrojích nepříliš povedená. Následně byly stanoveny hlavní požadavky a směr, kterým by se měl vývoj ubírat. Na začátku vývoje rekonstrukčního frameworku stála fáze vytvoření návrhu architektury a dekompozice průběhu zpracování zachycené komunikace do ucelených částí jednotlivých modulů. Využití předchozích znalostí a zkušeností získaných vývojem rekonstrukčního nástroje Reconsuite nám pomohlo při formování fronty zpracování, kterou budou data při zpracování procházet. Následně byly navrženy základní komponenty provádějící práci se zachycenou komunikací v různých formátech PCAP souborů, rozdělení komunikace na konverzace, provedení defragmentace na úrovni IP a v případě komunikace TCP provedení reassemblingu daných toků. V rané části vývoje jsme se zaměřili na komunikaci zapouzdřenou v nízkoúrovňových protokolech Ethernet, IPv4/IPv6, TCP a UDP. Po definici rozhraní komponent bylo nutné provést další výzkum síťových protokolů a vytvoření algoritmů pro jejich zpracování ze zachycené komunikace, která se liší od standardní a není tedy možné ji zpracovávat dobře známými postupy z RFC či jader operačních systémů. Protože proces zpracování zachycených dat se na komunikaci přímo nepodílí, tak v případě, kdy dojde ke ztrátě či poškození při zachycení, nebo je komunikace směřována jinou cestou, atd., není možné data získat pomocí znovu zasílání, ale je nutné využít jiné mechanismy k označení či obnově takto chybějících dat - algoritmus provádějící IP defragmentaci a TCP reassembling. Po implementaci a otestování byl zjištěn problém se separací jednotlivých TCP toků (TCP sessions), který nebylo možné řešit původním návrhem. Po analýze tohoto problému byla změněna architektura procesní pipeline s výsledným zvýšením počtu rekonstruovaných dat v desítkách procent. V závěrečné fázi je popsána metodologie jakou bylo porvedeno testování výkonu implementovaného řešení a srovnání s již existujícími nástroji. Protože rekonstrukce aplikačních dat je příliš specifická záležitost, při srovnání výkonu byla měřena rychlost zpracování a potřebná paměť pouze při provádění separace toků, IPv4 defragmentace a TCP reassemblingu, tedy operace společné pro všechny rekonstrukční nástroje. Srovnání ukázalo, že Netfox.Framework předčí své konkurenty Wireshark i Network monitor v rychlosti zpracování, tak v úspoře paměti. Jako testovací data byl použit jak generovaný provoz, tak i vzorky reálné komunikace zachycené v laboratorním prostředí.

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Cevik, Alper. "A Medical Image Processing And Analysis Framework." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12612965/index.pdf.

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Medical image analysis is one of the most critical studies in field of medicine, since results gained by the analysis guide radiologists for diagnosis, treatment planning, and verification of administered treatment. Therefore, accuracy in analysis of medical images is at least as important as accuracy in data acquisition processes. Medical images require sequential application of several image post-processing techniques in order to be used for quantification and analysis of intended features. Main objective of this thesis study is to build up an application framework, which enables analysis and quantification of several features in medical images with minimized input-dependency over results. Intended application targets to present a software environment, which enables sequential application of medical image processing routines and provides support for radiologists in diagnosis, treatment planning and treatment verification phases of neurodegenerative diseases and brain tumors
thus, reducing the divergence in results of operations applied on medical images. In scope of this thesis study, a comprehensive literature review is performed, and a new medical image processing and analysis framework - including modules responsible for automation of separate processes and for several types of measurements such as real tumor volume and real lesion area - is implemented. Performance of the fully-automated segmentation module is evaluated with standards introduced by Neuro Imaging Laboratory, UCLA
and the fully-automated registration module with Normalized Cross-Correlation metric. Results have shown a success rate above 90 percent for both of the modules. Additionally, a number of experiments have been designed and performed using the implemented application. It is expected for an accurate, flexible, and robust software application to be accomplished on the basis of this thesis study, and to be used in field of medicine as a contributor by even non-engineer professionals.

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Westin, Carl-Fredrik. "A Tensor Framework for Multidimensional Signal Processing." Doctoral thesis, Linköpings universitet, Bildbehandling, 1994. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54274.

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This thesis deals with ltering of multidimensional signals. A large part of the thesis is devoted to a novel filtering method termed "Normalized convolution". The method performs local expansion of a signal in a chosen lter basis which not necessarily has to be orthonormal. A key feature of the method is that it can deal with uncertain data when additional certainty statements are available for the data and/or the lters. It is shown how false operator responses due to missing or uncertain data can be significantly reduced or eliminated using this technique. Perhaps the most well-known of such eects are the various 'edge effects' which invariably occur at the edges of the input data set. The method is an example of the signal/certainty - philosophy, i.e. the separation of both data and operator into a signal part and a certainty part. An estimate of the certainty must accompany the data. Missing data are simply handled by setting the certainty to zero. Localization or windowing of operators is done using an applicability function, the operator equivalent to certainty, not by changing the actual operator coefficients. Spatially or temporally limited operators are handled by setting the applicability function to zero outside the window. The use of tensors in estimation of local structure and orientation using spatiotemporal quadrature filters is reviewed and related to dual tensor bases. The tensor representation conveys the degree and type of local anisotropy. For image sequences, the shape of the tensors describe the local structure of the spatiotemporal neighbourhood and provides information about local velocity. The tensor representation also conveys information for deciding if true flow or only normal flow is present. It is shown how normal flow estimates can be combined into a true flow using averaging of this tensor eld description. Important aspects of representation and techniques for grouping local orientation estimates into global line information are discussed. The uniformity of some standard parameter spaces for line segmentation is investigated. The analysis shows that, to avoid discontinuities, great care should be taken when choosing the parameter space for a particular problem. A new parameter mapping well suited for line extraction, the Möbius strip parameterization, is de ned. The method has similarities to the Hough Transform. Estimation of local frequency and bandwidth is also discussed. Local frequency is an important concept which provides an indication of the appropriate range of scales for subsequent analysis. One-dimensional and two-dimensional examples of local frequency estimation are given. The local bandwidth estimate is used for dening a certainty measure. The certainty measure enables the use of a normalized averaging process increasing robustness and accuracy of the frequency statements.

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張少能 and Siu-nang Bruce Cheung. "A concise framework of natural language processing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31208563.

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van, Schaik Sebastiaan Johannes. "A framework for processing correlated probabilistic data." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:91aa418d-536e-472d-9089-39bef5f62e62.

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The amount of digitally-born data has surged in recent years. In many scenarios, this data is inherently uncertain (or: probabilistic), such as data originating from sensor networks, image and voice recognition, location detection, and automated web data extraction. Probabilistic data requires novel and different approaches to data mining and analysis, which explicitly account for the uncertainty and the correlations therein. This thesis introduces ENFrame: a framework for processing and mining correlated probabilistic data. Using this framework, it is possible to express both traditional and novel algorithms for data analysis in a special user language, without having to explicitly address the uncertainty of the data on which the algorithms operate. The framework will subsequently execute the algorithm on the probabilistic input, and perform exact or approximate parallel probability computation. During the probability computation, correlations and provenance are succinctly encoded using probabilistic events. This thesis contains novel contributions in several directions. An expressive user language – a subset of Python – is introduced, which allows a programmer to implement algorithms for probabilistic data without requiring knowledge of the underlying probabilistic model. Furthermore, an event language is presented, which is used for the probabilistic interpretation of the user program. The event language can succinctly encode arbitrary correlations using events, which are the probabilistic counterparts of deterministic user program variables. These highly interconnected events are stored in an event network, a probabilistic interpretation of the original user program. Multiple techniques for exact and approximate probability computation (with error guarantees) of such event networks are presented, as well as techniques for parallel computation. Adaptations of multiple existing data mining algorithms are shown to work in the framework, and are subsequently subjected to an extensive experimental evaluation. Additionally, a use-case is presented in which a probabilistic adaptation of a clustering algorithm is used to predict faults in energy distribution networks. Lastly, this thesis presents techniques for integrating a number of different probabilistic data formalisms for use in this framework and in other applications.

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Cheung, Siu-nang Bruce. "A concise framework of natural language processing /." [Hong Kong : University of Hong Kong], 1989. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12432544.

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Karlsson, Per. "A GPU-based framework for efficient image processing." Thesis, Linköpings universitet, Medie- och Informationsteknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112093.

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This thesis tries to answer how to design a framework for image processing on the GPU, supporting the common environments OpenGL GLSL, OpenCL and CUDA. An generalized view of GPU image processing is presented. The framework is called gpuip and is implemented in C++ but also wrapped with Python-bindings. The framework is cross-platform and works for Windows, Mac OSX and Unix operating systems. The thesis also involves the work of creating two executable programs that uses the gpuip-framework. One of the programs has a graphical user interface and the other program is command-line only. Both programs are developed in Python. Performance tests are created to compare the GPU environments against a single core CPU implementation. All the GPU implementations in the gpuip-framework are significantly faster than the CPU when executing the presented test-cases. On average, the framework is two magnitudes faster than the single core CPU.

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Hongslo, Anders. "Stream Processing in the Robot Operating System framework." Thesis, Linköpings universitet, Artificiell intelligens och integrerad datorsystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79846.

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Streams of information rather than static databases are becoming increasingly important with the rapid changes involved in a number of fields such as finance, social media and robotics. DyKnow is a stream-based knowledge processing middleware which has been used in autonomous Unmanned Aerial Vehicle (UAV) research. ROS (Robot Operating System) is an open-source robotics framework providing hardware abstraction, device drivers, communication infrastructure, tools, libraries as well as other functionalities. This thesis describes a design and a realization of stream processing in ROS based on the stream-based knowledge processing middleware DyKnow. It describes how relevant information in ROS can be selected, labeled, merged and synchronized to provide streams of states. There are a lot of applications for such stream processing such as execution monitoring or evaluating metric temporal logic formulas through progression over state sequences containing the features of the formulas. Overviews are given of DyKnow and ROS before comparing the two and describing the design. The stream processing capabilities implemented in ROS are demonstrated through performance evaluations which show that such stream processing is fast and efficient. The resulting realization in ROS is also readily extensible to provide further stream processing functionality.

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Allott, Nicholas Mark. "A natural language processing framework for automated assessment." Thesis, Nottingham Trent University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.314333.

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Книги з теми "PROCESSING FRAMEWORK"

Singh, Rituraj. Pro Sync Framework. Berkeley, CA: Apress, 2009.

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Applied cognitive psychology: Aninformation-processing framework. London: Routledge, 1990.

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Framework applications. Blue Ridge Summit, PA: Tab Books, 1985.

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1941-, Fernandez Judi N., ed. Essential Framework. New York: Wiley, 1985.

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Mastering Framework. Berkeley: Sybex, 1985.

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Applied cognitive psychology: An information-processing framework. London: Methuen, 1988.

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Joydip, Kanjilal, ed. Pro Sync Framework. Berkeley, CA: Apress, 2009.

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H, Baker Richard, ed. Framework II applications. 2nd ed. Blue Ridge Summit, PA: Tab Books, 1987.

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McIntyre, Bruce. FRAMEWORK made easier. Englewood Cliffs, N.J: Prentice-Hall, 1985.

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MacInnis, Deborah J. Information processing from advertisements: Toward an integrative framework. Cambridge, Mass: Marketing Science Institute, 1990.

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Частини книг з теми "PROCESSING FRAMEWORK"

Machiraju, Srikanth, and Ritesh Modi. "Natural Language Processing." In Developing Bots with Microsoft Bots Framework, 203–32. Berkeley, CA: Apress, 2017. http://dx.doi.org/10.1007/978-1-4842-3312-2_9.

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Abbas, Abbas K., and Rasha Bassam. "PCG Signal Processing Framework." In Phonocardiography Signal Processing, 53–66. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-01637-0_3.

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Osherenko, Alexander. "Framework for Data Processing." In Human–Computer Interaction Series, 121–52. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-6260-5_5.

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Jerzak, Zbigniew, Anja Klein, and Gregor Hackenbroich. "GINSENG Data Processing Framework." In Reasoning in Event-Based Distributed Systems, 125–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19724-6_6.

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Kommadi, Bhagvan. "Quantum Information Processing Framework." In Quantum Computing Solutions, 69–110. Berkeley, CA: Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-6516-1_4.

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Rosinski, Lukasz. "Establish knowledge processing (framework)." In Knowledge Management for Project Excellence, 63–103. 1. Edition. | New York : Routledge, 2019.: Routledge, 2019. http://dx.doi.org/10.4324/9780429329975-6.

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Lyman, Forrest. "Building and Processing Web Forms with Zend_Form." In Pro Zend Framework Techniques, 37–52. Berkeley, CA: Apress, 2009. http://dx.doi.org/10.1007/978-1-4302-1880-7_3.

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Monteiro, Fernando C. "Hybrid Framework to Image Segmentation." In Neural Information Processing, 657–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-10684-2_73.

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Kimmel, Ron. "Geometric Framework in Image Processing." In Numerical Geometry of Images, 141–62. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-0-387-21637-9_10.

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Holambe, Raghunath S., and Mangesh S. Deshpande. "Nonlinearity Framework in Speech Processing." In SpringerBriefs in Electrical and Computer Engineering, 11–25. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-1505-3_2.

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Тези доповідей конференцій з теми "PROCESSING FRAMEWORK"

Vemula, Sridhar, and Christopher Crick. "Hadoop Image Processing Framework." In 2015 IEEE International Congress on Big Data (BigData Congress). IEEE, 2015. http://dx.doi.org/10.1109/bigdatacongress.2015.80.

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Weale, Timothy, Vijay Gadepally, Dylan Hutchison, and Jeremy Kepner. "Benchmarking the graphulo processing framework." In 2016 IEEE High Performance Extreme Computing Conference (HPEC). IEEE, 2016. http://dx.doi.org/10.1109/hpec.2016.7761640.

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Kota, Venkata Krishna, Thirumal Kumar Kanakurthi, T. Velayutham, M. Akila, and M. Hemavathy. "Secure Complex Event Processing Framework." In 2017 IEEE 7th International Advance Computing Conference (IACC). IEEE, 2017. http://dx.doi.org/10.1109/iacc.2017.0044.

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Gyurjyan, V., A. Bartle, C. Lukashin, S. Mancilla, R. Oyarzun, and A. Vakhnin. "Component based dataflow processing framework." In 2015 IEEE International Conference on Big Data (Big Data). IEEE, 2015. http://dx.doi.org/10.1109/bigdata.2015.7363971.

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Jung, Seungwoog, Choulsoo Jang, Byoungyoul Song, and Sunghoon Kim. "The OPRoS fault processing framework." In 2012 9th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2012. http://dx.doi.org/10.1109/urai.2012.6463004.

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Zhang, Xiangyu, Mengxiang Lin, and Kai Yu. "An integrated bug processing framework." In 2012 34th International Conference on Software Engineering (ICSE 2012). IEEE, 2012. http://dx.doi.org/10.1109/icse.2012.6227060.

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Twaty, Muaz, Amine Ghrab, and Sabri Skhiri. "GraphOpt: a Framework for Automatic Parameters Tuning of Graph Processing Frameworks." In 2019 IEEE International Conference on Big Data (Big Data). IEEE, 2019. http://dx.doi.org/10.1109/bigdata47090.2019.9006320.

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Major, Peter. "Image processing framework for traffic monitoring." In 2011 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2011. http://dx.doi.org/10.1109/aim.2011.6027139.

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Metwally, Eman S., Khalid Eskaf, and Walid M. Abdlmoez. "Signal Processing Framework for Interactive Architecture." In 2019 29th International Conference on Computer Theory and Applications (ICCTA). IEEE, 2019. http://dx.doi.org/10.1109/iccta48790.2019.9478807.

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Katibah, Ed. "Microsoft framework for geospatial stream processing." In the ACM SIGSPATIAL International Workshop. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878500.1878501.

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Звіти організацій з теми "PROCESSING FRAMEWORK"

Lennox, J., and H. Schulzrinne. Call Processing Language Framework and Requirements. RFC Editor, May 2000. http://dx.doi.org/10.17487/rfc2824.

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Hill, Jeffrey O. The LANSCE FPGA Embedded Signal Processing Framework. Office of Scientific and Technical Information (OSTI), October 2013. http://dx.doi.org/10.2172/1095850.

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Prescott, Ryan, and Benjamin R. Hamlet. US NDC Modernization Iteration E1 Prototyping Report: Processing Control Framework. Office of Scientific and Technical Information (OSTI), December 2014. http://dx.doi.org/10.2172/1173204.

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Musselman, Inga H. Novel Zeolitic Imidazolate Framework/Polymer Membranes for Hydrogen Separations in Coal Processing. Office of Scientific and Technical Information (OSTI), January 2013. http://dx.doi.org/10.2172/1091874.

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Rajagopalan, Ambasamudram N. Framework for Processing Videos in the Presence of Spatially Varying Motion Blur. Fort Belvoir, VA: Defense Technical Information Center, February 2016. http://dx.doi.org/10.21236/ada636878.

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M. Karrenbach. An Integrated Multi-component Processing and Interpretation Framework for 3D Borehole Seismic Data. Office of Scientific and Technical Information (OSTI), November 2005. http://dx.doi.org/10.2172/883087.

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Moreland, Kenneth, and Berk Geveci. A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale. Office of Scientific and Technical Information (OSTI), November 2014. http://dx.doi.org/10.2172/1164814.

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Ma, Kwan-Liu. A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale. Office of Scientific and Technical Information (OSTI), February 2017. http://dx.doi.org/10.2172/1341896.

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M. Karrenbach. AN INTEGRATED MULTI-COMPONENT PROCESSING AND INTERPRETATION FRAMEWORK FOR 3D BOREHOLE SEISMIC DATA. Office of Scientific and Technical Information (OSTI), April 2005. http://dx.doi.org/10.2172/842641.

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