Search results for "Artificial"

showing 10 items of 7394 documents

Temporal Denoising of Kinect Depth Data

2012

The release of the Microsoft Kinect has attracted the attention of researchers in a variety of computer science domains. Even though this device is still relatively new, its recent applications have shown some promising results in terms of replacing current conventional methods like the stereo-camera for robotics navigation, multi-camera system for motion detection and laser scanner for 3D reconstruction. While most work around the Kinect is on how to take full advantage of its capabilities, so far only a few studies have been carried out on the limitations of this device and fewer that provide solutions to enhance the precision of its measurements. In this paper, we review and analyse curr…

depth measurement[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingLaser scanning[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceNoise reductionDenoising algorithmComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technology[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingtemporal denoising0202 electrical engineering electronic engineering information engineeringComputer visionImage denoisingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingbusiness.industry3D reconstruction020206 networking & telecommunicationsRoboticsMotion detectionKinect depth dataMicrosoft Kinect020201 artificial intelligence & image processingArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing2012 Eighth International Conference on Signal Image Technology and Internet Based Systems
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Régimen jurídico de la toma de decisiones automatizadas y el uso de sistemas de inteligencia artificial en el marco del derecho a la protección de da…

2021

El objetivo general que pretendemos con esta tesis es analizar y clarificar el régimen jurídico aplicable a las decisiones automatizadas con relación al derecho fundamental a la protección de datos personales. No sólo se abordan las cuestiones relacionadas con las decisiones estrictamente automatizadas sino también aquellas decisiones que sin ser plenamente automatizadas, se utilizan como apoyo a la decisión que finalmente adopta un humano. La automatización del proceso decisorio a través de algoritmos plantea toda una serie de retos jurídicos que afectan directamente a los derechos y libertades de las personas. La normativa en materia de protección de datos se muestra como una de las princ…

derecho a la protección de datos personalesdecisiones automatizadasinteligencia artificialalgoritmo:CIENCIAS JURÍDICAS Y DERECHO [UNESCO]UNESCO::CIENCIAS JURÍDICAS Y DERECHOelaboración de perfiles
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Extraction et évaluation de caractéristiques adaptées pour la classification du Lentigo à partir d’images de Microscopie Confocale

2019

International audience; La détection de cancer de la peau est l’un des défis de ces dernières décennies. Par ailleurs, diverses techniques d’imagerie ont pour objectif d’aider à la reconnaissance de ces pathologies malignes en contexte clinique. La Microscopie Confocale par Réflectance est un exemple de technique d’imagerie adaptée à la détection de maladie de la peau sur laquelle nous nous basons pour la détection de Lentigo. Les travaux présentés dans cet article portent sur la classification de ces images en trois catégories : sain, bénin et malin. Dans ce but, nous proposons et évaluons deux méthodes d’extraction de caractéristiques basées sur les descripteurs d’Haralick pour l’une et s…

dermatology[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]classification[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical Imaginglentigo[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Reflectance Confocal Microscopy
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Artificial intelligence in the diagnosis of pediatric allergic diseases.

2020

Abstract: Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with the human world. Early diagnosis and diagnostics, self-care, prevention and wellness, clinical decision support, care delivery, and chronic care management have been identified within the healthcare areas that could benefit from introducing AI. In pediatric allergy research, the recent developments in AI approach provided new perspectives for characterizing the heterogeneity of allergic diseases among patients. Moreover, the increasing use of electronic health records and personal healthcare records highlighted the relevance of AI in …

diagnosisChronic care managementImmunologyClinical decision support systemField (computer science)03 medical and health sciencesSettore MED/38 - Pediatria Generale E Specialistica0302 clinical medicinechildrenArtificial IntelligenceHealth careHypersensitivityrespiratory allergyImmunology and AllergyMedicineElectronic Health RecordsHumansRelevance (information retrieval)030212 general & internal medicineChildfood allergybusiness.industryRespiratory allergyallergydiagnosi030228 respiratory systemData qualityPediatrics Perinatology and Child HealtheczemaArtificial intelligencePediatric allergybusinessDelivery of Health CareAlgorithmsPediatric allergy and immunology : official publication of the European Society of Pediatric Allergy and ImmunologyREFERENCES
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Artificial Intelligence in Medicine: Today and Tomorrow

2020

Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a mor…

digital medicineComputer sciencemedia_common.quotation_subjectWearable computerScientific literature030204 cardiovascular system & hematology03 medical and health sciences0302 clinical medicineHealth careMedical imaging030212 general & internal medicinemobile healthmedia_commonmedical technologieslcsh:R5-920business.industryGénéralitésGeneral MedicineBioethicsartificial intelligenceClinical trialmonitoringPerspectiveMedicineArtificial intelligenceApplications of artificial intelligencebusinesslcsh:Medicine (General)AutonomyFrontiers in Medicine
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Socio-digital intervention: Towards what future do we want to walk to?

2021

Este documento pretende ser una aproximación a cómo la digitalización puede modificar a intervención social debido a los recientes desarrollos en la inteligencia artificial. El objeto de investigación se centra en el marco de los servicios sociales, y en concreto en la figura del Trabajo Social, sin embargo, los hallazgos encontrados son generalizables a cualquier disciplina que opere en la intervención social (Psicología Social, Educadores Sociales, Pedagogía, Animación Sociocultural, etc.). Transitaremos por las perspectivas teóricas y cosmovisiones científicas que analizan la relación tecnología-sociedad, con el objetivo de enmarcar el presente estudio y disponer de marcos interpretativo…

digitalizaciónservicios socialesintervención socialinteligencia artificialUNESCO::SOCIOLOGÍAtrabajo socialSociología
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Linear Feature Extraction for Ranking

2018

We address the feature extraction problem for document ranking in information retrieval. We then propose LifeRank, a Linear feature extraction algorithm for Ranking. In LifeRank, we regard each document collection for ranking as a matrix, referred to as the original matrix. We try to optimize a transformation matrix, so that a new matrix (dataset) can be generated as the product of the original matrix and a transformation matrix. The transformation matrix projects high-dimensional document vectors into lower dimensions. Theoretically, there could be very large transformation matrices, each leading to a new generated matrix. In LifeRank, we produce a transformation matrix so that the generat…

dimension reductionComputer scienceFeature extractionMathematicsofComputing_NUMERICALANALYSISFeature selectiontiedonhakujärjestelmät02 engineering and technologyLibrary and Information SciencesRanking (information retrieval)Matrix (mathematics)Transformation matrix020204 information systemsalgoritmit0202 electrical engineering electronic engineering information engineeringtiedonhakulearning to rankbusiness.industryfeature extractionPattern recognitionkoneoppiminenPattern recognition (psychology)Benchmark (computing)020201 artificial intelligence & image processingLearning to rankArtificial intelligencebusinessInformation Systems
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Integration of large-area optical imagers for biometric recognition and touch in displays

2021

In recent years there has been an increasing interest to integrate optical sensing in mobile displays, for instance, for biometric fingerprint scanning functionality. There are several routes to incorporate optical fingerprint functionality within the full display area, each with their own benefits and challenges. Here we investigate the different integration routes using large-area, ultra-thin imagers based on organic photodiodes.

display integrationbiometricsMaterials scienceBiometricsgenetic structuresbusiness.industrylarge-area imagerComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONFingerprint recognitionfingerprint scannerAtomic and Molecular Physics and Opticseye diseasesElectronic Optical and Magnetic MaterialsAMOLEDAMOLEDComputer visionArtificial intelligencesense organsElectrical and Electronic Engineeringbusinessoptical sensorOPDorganic photodiodeJournal of the Society for Information Display
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A Dataset of Annotated Omnidirectional Videos for Distancing Applications

2021

Omnidirectional (or 360°) cameras are acquisition devices that, in the next few years, could have a big impact on video surveillance applications, research, and industry, as they can record a spherical view of a whole environment from every perspective. This paper presents two new contributions to the research community: the CVIP360 dataset, an annotated dataset of 360° videos for distancing applications, and a new method to estimate the distances of objects in a scene from a single 360° image. The CVIP360 dataset includes 16 videos acquired outdoors and indoors, annotated by adding information about the pedestrians in the scene (bounding boxes) and the distances to the camera of some point…

distancingComputer scienceDistancing360°Computer applications to medicine. Medical informaticsComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONR858-859.7Pedestrianvideo datasetArticleImage (mathematics)Bounding overwatchResearch communityomnidirectional camerasdepth estimationPhotographyRadiology Nuclear Medicine and imagingComputer visionvideo surveillanceElectrical and Electronic EngineeringOmnidirectional antennaTR1-1050360Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionispherical imagesbusiness.industryPerspective (graphical)Process (computing)QA75.5-76.95trackingComputer Graphics and Computer-Aided Designequirectangular projectionElectronic computers. Computer sciencepedestrianComputer Vision and Pattern RecognitionArtificial intelligencebusinessJournal of Imaging
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Decentralized classification in societies of autonomous and heterogenous robots

2011

This paper addresses the classification problem for a set of autonomous robots that interact with each other. The objective is to classify agents that “behave” in “different way”, due to their own physical dynamics or to the interaction protocol they are obeying to, as belonging to different “species”. This paper describes a technique that allows a decentralized classification system to be built in a systematic way, once the hybrid models describing the behavior of the different species are given. This technique is based on a decentralized identification mechanism, by which every agent classifies its neighbors using only local information. By endowing every agent with such a local classifie…

distributed algorithm0106 biological sciencesSpecies classification0209 industrial biotechnologyEngineeringbusiness.industrymulti-robot systemInteraction protocolRoboticsMobile robot02 engineering and technologyAutonomous robotconsensus protocols010603 evolutionary biology01 natural sciencesComputer Science::Multiagent SystemsIdentification (information)020901 industrial engineering & automationSettore ING-INF/04 - AutomaticaRobotArtificial intelligenceSet (psychology)businessClassifier (UML)2011 IEEE International Conference on Robotics and Automation
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