Search results for "intelligence"

showing 10 items of 6959 documents

Actes CNIA 2018 - Conférence Nationale d'Intelligence Artificielle

2018

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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Sub-optimal waypoints, UAV path planning and mosaicing application

2016

International audience; Create a complete system of video surveillance using camera mounted on a robot like UAV to maintain optimized vast area coverage and reconstruct an image by using mosaicing techniques. This paper demonstrated the efficiency of using one UAV to cover vast area using optimized positions.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Cover (telecommunications)Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION010103 numerical & computational mathematics01 natural sciencesUnmanned aerial vehicles[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionMotion planning0101 mathematics[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Genetic Algorithmbusiness.industry[ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO][INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][SPI.TRON] Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/Electronics010101 applied mathematicsCoverage path planningArea coverageRobotArtificial intelligencebusiness
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Research and implementation of artificial neural networks models for high velocity oxygen fuel thermal spraying

2020

In the high velocity oxygen fuel (HVOF) spray process, the coating properties are sensitive to the characteristics of in-flight particles, which are mainly determined by the process parameters. Due to the complex chemical and thermodynamic reactions during the deposition procedure, obtaining a comprehensive multi-physical model or analytical analysis of the HVOF process is still a challenging issue. This study proposes to develop a robust methodology via artificial neural networks (ANN) to solve this problem for the HVOF sprayed NiCr-Cr3C2 coatings under different operating parameters.First, 40 sets of HVOF spray experiments were conducted and the coating properties were tested for analysis…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Cr3C2-NiCrArtificial intelligenceArtificial neural networksRéseaux de neurones artificielsHvofIntelligence artificielle[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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Semantic User Profiling for Digital Advertising

2015

International audience; With the emergence of real-time distribution of online advertising space (“real-time bidding”), user profiling from web navigation traces becomes crucial. Indeed, it allows online advertisers to target customers without interfering with their activities. Current techniques apply traditional methods as statistics and machine learning, but suffer from their limitations. As an answer, the proposed approach aims to develop and evaluate a semantic-based user profiling system for digital advertising.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Data AnalysisBig DataACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[ INFO ] Computer Science [cs]OntologyACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingACM : H.: Information SystemsUser ProfilingACM: H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONSReasoningACM : H.: Information Systems/H.4: INFORMATION SYSTEMS APPLICATIONS[INFO] Computer Science [cs][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]ACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesACM: H.: Information SystemsInferenceACM : H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.5: Online Information Services[INFO]Computer Science [cs]Logical Rules[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.1: Content Analysis and IndexingSWRLACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.4: Systems and Software/H.3.4.5: User profiles and alert servicesSemantic Web
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TOWARDS SEMANTIC INTEROPERABILITY FOR ENTERPRISE INFORMATION SYSTEMS

2016

International audience; In the context of globalisation, data and knowledge management, and given the need to deliver a quick response to changes in market forces, enterprises have to collaborate using information technologies to succeed in a disparate and dynamical business environment. Enterprise interoperability (EI) is a field of study that aims to improve this collaboration. Moreover, EI addresses problems related to the lack of system interoperability in organisations. In this paper, we focus on approaches which deliver semantic interoperability among enterprise information systems. We conclude by identifying the main drawbacks of such approaches to be adopted by world-wide industry a…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Enterprise InteroperabilityModel-driven Interoperability (MDI)ontology[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]semantic interoperability[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

2020

L'analyse prédictive permet d'estimer les tendances des évènements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes prédictions. Cependant, pour chaque type de problème donné, il est nécessaire de choisir l'architecture optimale. Dans cet article, les modèles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqués à une série temporelle d'images radar sentinel-1, le but étant de prédire la prochaine occurrence dans une séquence. Les résultats expérimentaux évalués à l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarité SSIM, montrent que chacune des trois architectures peut produire de bons résultats en fon…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesApprentissage profondComputer Science - Machine LearningImage and Video Processing (eess.IV)[INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]PrévisionComputer Science - Neural and Evolutionary ComputingDeep Learning AlgorithmsPrédiction[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]Electrical Engineering and Systems Science - Image and Video ProcessingLand cover change[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)SARIMA[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]FOS: Electrical engineering electronic engineering information engineeringSatellite imagesNeural and Evolutionary Computing (cs.NE)LSTMPredictionForecastingImages satellitaires
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hidden markov random fields and cuckoo search method for medical image segmentation

2020

Segmentation of medical images is an essential part in the process of diagnostics. Physicians require an automatic, robust and valid results. Hidden Markov Random Fields (HMRF) provide powerful model. This latter models the segmentation problem as the minimization of an energy function. Cuckoo search (CS) algorithm is one of the recent nature-inspired meta-heuristic algorithms. It has shown its efficiency in many engineering optimization problems. In this paper, we use three cuckoo search algorithm to achieve medical image segmentation.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesComputer Science - Machine LearningComputer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)FOS: Electrical engineering electronic engineering information engineeringComputer Science - Computer Vision and Pattern RecognitionElectrical Engineering and Systems Science - Image and Video Processing[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)
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Unsupervised learning of category-specific symmetric 3D keypoints from point sets

2020

Lecture Notes in Computer Science, 12370

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesComputer sciencePlane symmetryComputer Vision and Pattern Recognition (cs.CV)Point cloudComputer Science - Computer Vision and Pattern Recognition02 engineering and technology010501 environmental sciences01 natural sciences[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Linear basis0202 electrical engineering electronic engineering information engineeringComputingMilieux_COMPUTERSANDEDUCATIONPoint (geometry)0105 earth and related environmental sciencesbusiness.industryCategory specific[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Pattern recognition16. Peace & justiceBenchmark (computing)Unsupervised learning020201 artificial intelligence & image processingArtificial intelligenceSymmetry (geometry)business
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3D landmark detection for augmented reality based otologic procedures

2019

International audience; Ear consists of the smallest bones in the human body and does not contain significant amount of distinct landmark points that may be used to register a preoperative CT-scan with the surgical video in an augmented reality framework. Learning based algorithms may be used to help the surgeons to identify landmark points. This paper presents a convolutional neural network approach to landmark detection in preoperative ear CT images and then discusses an augmented reality system that can be used to visualize the cochlear axis on an otologic surgical video.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciences[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Computer Vision and Pattern Recognition (cs.CV)Image and Video Processing (eess.IV)Computer Science - Computer Vision and Pattern Recognition[INFO.INFO-IM] Computer Science [cs]/Medical ImagingFOS: Electrical engineering electronic engineering information engineering[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Electrical Engineering and Systems Science - Image and Video Processing[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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FOWLA, A Federated Architecture for Ontologies.

2015

International audience; The progress of information and communication technologies has greatly increased the quantity of data to process. Thus, managing data heterogeneity is a problem nowadays. In the 1980s, the concept of a Federated Database Architecture (FDBA) was introduced as a collection of components to unite loosely coupled federation. Semantic web technologies mitigate the data heterogeneity problem, however due to the data structure heterogeneity the integration of several ontologies is still a complex task. For tackling this problem, we propose a loosely coupled federated ontology architecture (FOWLA). Our approach allows the coexistence of various ontologies sharing common data…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Federated Ontology ArchitectureComputer scienceProcess (engineering)Distributed computing[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]Ontology (information science)SPARQL[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]World Wide WebSPARQLArchitecture[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Semantic WebComputingMilieux_MISCELLANEOUSSWRLOWLHorn-like rules[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]computer.file_formatSemantic interoperabilityData structuresemantic interoperabilitybackward-chaining reasoningInformation and Communications Technologycomputer
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