Search results for " Retrieval"

showing 10 items of 1114 documents

Saliency in spectral images

2011

International audience; Even though the study of saliency for color images has been thoroughly investigated in the past, very little attention has been given to datasets that cannot be displayed on traditional computer screens such as spectral images. Nevertheless, more than a means to predict human gaze, the study of saliency primarily allows for measuring infor- mative content. Thus, we propose a novel approach for the computation of saliency maps for spectral images. Based on the Itti model, it in- volves the extraction of both spatial and spectral features, suitable for high dimensionality images. As an application, we present a comparison framework to evaluate how dimensionality reduct…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer scienceComputation0211 other engineering and technologiesComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingImage (mathematics)[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingInformative content0202 electrical engineering electronic engineering information engineeringVisual attentionComputer visionRelevance (information retrieval)spectral images[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing021101 geological & geomatics engineeringSaliencybusiness.industryDimensionality reductionPattern recognitionKadir–Brady saliency detector020201 artificial intelligence & image processingArtificial intelligenceHigh dimensionalitybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
researchProduct

Ontology-driven Image Analysis for Histopathological Images

2010

International audience; Ontology-based software and image processing engine must cooperate in new fields of computer vision like microscopy acquisition wherein the amount of data, concepts and processing to be handled must be properly controlled. Within our own platform, we need to extract biological objects of interest in huge size and high-content microscopy images. In addition to specific low-level image analysis procedures, we used knowledge formalization tools and high-level reasoning ability of ontology-based software. This methodology made it possible to improve the expressiveness of the clinical models, the usability of the platform for the pathologist and the sensitivity or sensibi…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingComputer science[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONImage processingOntology (information science)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imaging03 medical and health sciences[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]0302 clinical medicineSoftware[STAT.AP] Statistics [stat]/Applications [stat.AP][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingDigital image processing[ INFO.INFO-TI ] Computer Science [cs]/Image Processing[INFO.INFO-IM]Computer Science [cs]/Medical ImagingComputer visionRDFImage analysis[STAT.AP]Statistics [stat]/Applications [stat.AP]Information retrieval[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industry[ STAT.AP ] Statistics [stat]/Applications [stat.AP][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Usabilitycomputer.file_formatAutomatic image annotation[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]030220 oncology & carcinogenesis[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Artificial intelligencebusinesscomputer
researchProduct

Cross-Media Color Reproduction and Display Characterization

2012

International audience; In this chapter, we present the problem of cross-media color reproduction, that is, how to achieve consistent reproduction of images in different media with different technologies. Of particular relevance for the color image processing community is displays, whose color properties have not been extensively covered in previous literature. Therefore, we go more in depth concerning how to model displays in order to achieve colorimetric consistency. The structure of this chapter is as follows: After a short introduction, we introduce the field of cross-media color reproduction, including a brief description of current standards for color management, the concept of colori…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONColor reproductionCross media[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyBiologyColor management01 natural sciencesCharacterization (materials science)law.invention010309 opticsConsistency (database systems)[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processinglaw0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingColor image processingRelevance (information retrieval)Computer visionArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
researchProduct

A Use Case of Data Integration in Food Production

2018

International audience; This paper presents a use case about knowledge representation and integration of data from different domains in food science. An ontology named PO 2 DG, the Process and Observation Ontology for the production of Dairy Gels, has been designed in order to provide a shared vocabulary for domain experts. The available data have been semantically structured using PO 2 DG and are stored in an RDF repository named PO 2 DG dataset. This use case identifies some of the challenges when dealing with a multi domain representation problem, gives some hints about possible solutions and suggests some further work.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]ACM: H.: Information Systems/H.3: INFORMATION STORAGE AND RETRIEVAL/H.3.3: Information Search and Retrievalexperimental observations represen- tationontology based data integrationprocess representation[INFO.INFO-WB] Computer Science [cs]/WebACM: H.: Information Systems[INFO.INFO-WB]Computer Science [cs]/Web[INFO]Computer Science [cs][INFO] Computer Science [cs]food science[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
researchProduct

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
researchProduct

Enhancing scientific information systems with semantic annotations

2013

International audience; Scientific Information Systems aim to produce or improve knowledge on a subject through activities of research and development. The management of scientific dat a requires some essential properties. We propose SemLab an architecture that sup ports interoperability, data quality and extensibility through a unique paradigm: semantic annotation. We present two app lications that validate our architecture.

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Information retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB][INFO.INFO-WB] Computer Science [cs]/WebComputer scienceInteroperability[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/WebSubject (documents)02 engineering and technologyOntology (information science)Semantic interoperabilityData science[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]020204 information systemsData qualitySemantic computing0202 electrical engineering electronic engineering information engineeringInformation system[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]020201 artificial intelligence & image processing[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]
researchProduct

Representing and Reasoning for Spatiotemporal Ontology Integration

2004

International audience; The World-Wide Web hosts many autonomous and heterogeneous information sources. In the near future each source may be described by its own ontology. The distributed nature of ontology development will lead to a large number of local ontologies covering overlapping domains. Ontology integration will then become an essential capability for effective interoperability and information sharing. Integration is known to be a hard problem, whose complexity increases particularly in the presence of spatiotemporal information. Space and time entail additional problems such as the heterogeneity of granularity used in representing spatial and temporal features. Spatio-temporal ob…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Information retrieval[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO]Computer scienceOntologyProcess ontologyOntology-based data integrationSuggested Upper Merged OntologyIntegration[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]Spatio-Temporal data02 engineering and technologyOntology (information science)[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Open Biomedical OntologiesMapping020204 information systemsOntology components0202 electrical engineering electronic engineering information engineeringUpper ontology020201 artificial intelligence & image processingOntology alignment
researchProduct

Continuum : un modèle spatio-temporel et sémantique pour la découverte de phénomènes dynamiques au sein d’environnements géospatiaux

2015

There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a model to discover knowledg…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-TT ] Computer Science [cs]/Document and Text Processing[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-WB] Computer Science [cs]/WebOntology[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-TT] Computer Science [cs]/Document and Text Processingdynamiques spatio-temporelles[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-TT]Computer Science [cs]/Document and Text Processingmodélisation et raisonnement spatial qualitatif[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Système d’Information Géographique[ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]système d’aide à la décisionanalyse géospatiale[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ontologie
researchProduct

Multi-Domain Retrieval of Geospatial Data Sources Implementing a Semantic Catalogue

2015

International audience; Nowadays, the expertise of a user plays an important role in the search and retrieval in the information systems that usually combines general and specialized knowledge in the construction of queries. In addition, most of the queries systems are currently restricted on specific domains. Tackling these issues, we propose a methodology that implements a semantic catalogue in order to provide a smart queries system for retrieving data sources on the web by means of the extension of the user expertise. We propose the combination of a query expansion method, and the use of similarity measures and controlled vocabularies. Thus, it allows the system to recommend data source…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-TT ] Computer Science [cs]/Document and Text Processing[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-WB] Computer Science [cs]/Web[INFO.INFO-WB]Computer Science [cs]/Websimilarity across ontologies.[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO]multi-domain retrievalsmart queries[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]: Semantic catalogue[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]knowledge engineering
researchProduct

Multidimensional Land Cover Change Analysis using Vector Change and Land Cover Taxonomies

2015

International audience; Around the world, land cover changes occur due to natural and anthropogenic factors. In many cases, the consequences of anthropogenic interventions are unexpected. In order for scientists and policy makers to identify land cover change processes of interest, it is necessary suitable tools for early and efficient analysis of land cover data. In our research, we present a data model that makes use of semantic web technologies to manage a hierarchical structure of land cover types. Using this approach, it is possible to manage the land cover information at different levels of abstraction. In our research, we use a Change Vector Analysis approach to represent the land co…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-TT ] Computer Science [cs]/Document and Text Processingdescription logics[INFO.INFO-LO] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-WB] Computer Science [cs]/Webspatio-temporal[INFO.INFO-WB]Computer Science [cs]/Web[ INFO.INFO-WB ] Computer Science [cs]/Web[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing[INFO.INFO-LO]Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-TT]Computer Science [cs]/Document and Text Processingland cover[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-LO ] Computer Science [cs]/Logic in Computer Science [cs.LO][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]
researchProduct