Search results for " Computer Science"

showing 10 items of 3983 documents

DPLL with restarts linearly simulates CDCL

2019

If we give DPLL the ability to make restarts and to learn clauses representing the explored search space, it can linearly simulate CDCL solvers.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]CDCLDPLLSATrestart[INFO] Computer Science [cs]
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Automatic Timeline Construction and Analysis For Computer Forensics Purposes

2014

International audience; To determine the circumstances of an incident, investigators need to reconstruct events that occurred in the past. The large amount of data spread across the crime scene makes this task very tedious and complex. In particular, the analysis of the reconstructed timeline, due to the huge quantity of events that occurred on a digital system, is almost impossible and leads to cognitive overload. Therefore, it becomes more and more necessary to develop automatic tools to help or even replace investigators in some parts of the investigation. This paper introduces a multi-layered architecture designed to assist the investigative team in the extraction of information left in…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Computer science[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Digital forensicsEvent ReconstructionOntology (information science)Computer securitycomputer.software_genre[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Task (project management)[INFO.INFO-CY]Computer Science [cs]/Computers and Society [cs.CY]Timeline AnalysisCrime scene[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]Event reconstructionOntologyTimelineComputer forensics16. Peace & justiceData science[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH][ INFO.INFO-CY ] Computer Science [cs]/Computers and Society [cs.CY]Digital Forensics[INFO.INFO-CY] Computer Science [cs]/Computers and Society [cs.CY][ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]computerCognitive load
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6th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty

2001

International audience; no abstract

[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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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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