Search results for "Information system"

showing 10 items of 2404 documents

Open Set Audio Classification Using Autoencoders Trained on Few Data.

2020

Open-set recognition (OSR) is a challenging machine learning problem that appears when classifiers are faced with test instances from classes not seen during training. It can be summarized as the problem of correctly identifying instances from a known class (seen during training) while rejecting any unknown or unwanted samples (those belonging to unseen classes). Another problem arising in practical scenarios is few-shot learning (FSL), which appears when there is no availability of a large number of positive samples for training a recognition system. Taking these two limitations into account, a new dataset for OSR and FSL for audio data was recently released to promote research on solution…

Computer scienceOpen set02 engineering and technologylcsh:Chemical technologyMachine learningcomputer.software_genreBiochemistryArticleAnalytical ChemistrySet (abstract data type)open set recognition020204 information systemsaudio classificationautoencoders0202 electrical engineering electronic engineering information engineeringFeature (machine learning)lcsh:TP1-1185few-shot learningElectrical and Electronic EngineeringRepresentation (mathematics)Instrumentationbusiness.industryopen set classificationPerceptronClass (biology)AutoencoderAtomic and Molecular Physics and OpticsEmbedding020201 artificial intelligence & image processingArtificial intelligenceTransfer of learningbusinesscomputerSensors (Basel, Switzerland)
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Set similarity joins on mapreduce

2018

Set similarity joins, which compute pairs of similar sets, constitute an important operator primitive in a variety of applications, including applications that must process large amounts of data. To handle these data volumes, several distributed set similarity join algorithms have been proposed. Unfortunately, little is known about the relative performance, strengths and weaknesses of these techniques. Previous comparisons are limited to a small subset of relevant algorithms, and the large differences in the various test setups make it hard to draw overall conclusions. In this paper we survey ten recent, distributed set similarity join algorithms, all based on the MapReduce paradigm. We emp…

Computer scienceProcess (engineering)General EngineeringJoinsScale (descriptive set theory)02 engineering and technologycomputer.software_genreSet (abstract data type)Range (mathematics)Operator (computer programming)Similarity (network science)020204 information systems0202 electrical engineering electronic engineering information engineeringJoin (sigma algebra)020201 artificial intelligence & image processingData miningcomputerProceedings of the VLDB Endowment
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Special issue on architectures of smart cameras for real-time applications

2016

Smart cameras are embedded vision systems whose primary function is to produce a semantic understanding of the scene and generate a response in the form of application-specific signals and data. They are autonomous vision systems themselves and can be the building blocks of a more complex smart camera network. They are built around high-performance on-chip and on-board computing and communication infrastructure, combining image sensing, real-time image and video processing, and communications into a single embedded device. They can also be interconnected in networks and cooperate to provide access to many views, enabling more challenging applications in fields like visual control, surveilla…

Computer scienceReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.TRON ] Engineering Sciences [physics]/Electronics[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.TRON]Engineering Sciences [physics]/ElectronicsComputer graphics[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingPattern recognition (psychology)Multimedia information systemsSmart camera[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSInformation SystemsJournal of Real-Time Image Processing
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Refining a Reference Architecture for Model-Driven Business Apps

2016

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Computer scienceRefiningbusiness.industry020204 information systems0202 electrical engineering electronic engineering information engineering020207 software engineering02 engineering and technologyReference architectureData miningcomputer.software_genreSoftware engineeringbusinesscomputer
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Session details: Volume I: Artificial intelligence & agents, distributed systems, and information systems: data mining track

2013

Computer scienceTrack (disk drive)Real-time computingVolume (computing)Information systemSession (computer science)Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Grammars++ for modelling information in text

1999

Abstract Grammars provide a convenient means to describe the set of valid instances in a text database. Flexibility in choosing a grammar can be exploited to provide information modelling capability by designing productions in the grammar to represent entities and relationships of interest to database applications. Additional constraints can be specified by attaching predicates to selected nonterminals in the grammar. When used for database definition, grammars can provide the functionality that users have come to expect of database schemas. Extended grammars can also be used to specify database manipulation, including query, update, view definition, and index specification.

Computer scienceViewmedia_common.quotation_subjectComputerApplications_COMPUTERSINOTHERSYSTEMScomputer.software_genreQuery languageDatabase designAdaptive grammarRule-based machine translationmedia_commonGrammarProgramming languagebusiness.industryDatabase schemaPredicate (grammar)TheoryofComputation_MATHEMATICALLOGICANDFORMALLANGUAGESExtended Affix GrammarHardware and ArchitectureAffix grammarStochastic context-free grammarSynchronous context-free grammarArtificial intelligenceL-attributed grammarbusinesscomputerSoftwareNatural language processingInformation SystemsInformation Systems
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Non-speech voice for sonic interaction: a catalogue

2016

This paper surveys the uses of non-speech voice as an interaction modality within sonic applications. Three main contexts of use have been identified: sound retrieval, sound synthesis and control, and sound design. An overview of different choices and techniques regarding the style of interaction, the selection of vocal features and their mapping to sound features or controls is here displayed. A comprehensive collection of examples instantiates the use of non-speech voice in actual tools for sonic interaction. It is pointed out that while voice-based techniques are already being used proficiently in sound retrieval and sound synthesis, their use in sound design is still at an exploratory p…

Computer scienceVoice - Sonic interaction - Information retrieval - Sound synthesis - Sound designSpeech recognitionSound design02 engineering and technologyExploratory phase020204 information systemsSonic interaction design0202 electrical engineering electronic engineering information engineeringSelection (linguistics)Information retrieval0501 psychology and cognitive sciences050107 human factorsSound (geography)Sonic interactiongeographyModality (human–computer interaction)geography.geographical_feature_categoryInformation retrieval; Sonic interaction; Sound design; Sound synthesis; Voice; Signal Processing; Human-Computer InteractionSettore INF/01 - Informatica05 social sciencesSound synthesiSound designHuman-Computer InteractionSignal ProcessingVoice
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MAC Protocols for Wake-up Radio: Principles, Modeling and Performance Analysis

2018

[EN] In wake-up radio (WuR) enabled wireless sensor networks (WSNs), a node triggers a data communication at any time instant by sending a wake-up call (WuC) in an on-demand manner. Such wake-up operations eliminate idle listening and overhearing burden for energy consumption in duty-cycled WSNs. Although WuR exhibits its superiority for light traffic, it is inefficient to handle high traffic load in a network. This paper makes an effort towards improving the performance of WuR under diverse load conditions with a twofold contribution. We first propose three protocols that support variable traffic loads by enabling respectively clear channel assessment (CCA), backoff plus CCA, and adaptive …

Computer scienceWireless sensor networks (WSNs)02 engineering and technology01 natural sciencesWake-up radio (WuR)Medium access control (MAC) protocol0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringLatency (engineering)QueueEnergy-efficient communicationbusiness.industryNode (networking)010401 analytical chemistryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS020206 networking & telecommunicationsEnergy consumptionINGENIERIA TELEMATICA0104 chemical sciencesComputer Science ApplicationsInternet of Things (IoT)Variable (computer science)Modeling and performance evaluationControl and Systems EngineeringbusinessWireless sensor networkInformation SystemsComputer networkEfficient energy useData transmission
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Information flow and WOM in social media and online communities

2017

Computer sciencebusiness.industry05 social sciencesInternet privacyLibrary and Information SciencesComputer Science Applications0502 economics and business050211 marketingSocial mediaInformation flow (information theory)0509 other social sciences050904 information & library sciencesbusinessInformation SystemsOnline Information Review
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Feature selection with Ant Colony Optimization and its applications for pattern recognition in space imagery

2016

This paper presents a feature selection (FS) algorithm using Ant Colony Optimization (ACO). It is inspired by the particular behavior of real ants, namely by the fact that they are capable of finding the shortest path between a food source and the nest. There are considered two ACO-FS model applications for pattern recognition in remote sensing imagery: ACO Band Selection (ACO-BS) and ACO Training Label Purification (ACO-TLP). The ACO-BS reduces dimensionality of an input multispectral image data by selecting the “best” subset of bands to accomplish the classification task. The ACO-TLP selects the most informative training samples from a given set of labeled vectors in order to optimize the…

Computer sciencebusiness.industryAnt colony optimization algorithmsMultispectral imageFeature selectionPattern recognition02 engineering and technologyStatistical classification020204 information systemsPrincipal component analysisShortest path problem0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)Curse of dimensionality2016 International Conference on Communications (COMM)
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