Scan Science and Technology
Contact Leading Edge Experts & Companies
Atomic Concept
The Experts below are selected from a list of 120 Experts worldwide ranked by ideXlab platform
Jianqiang Wang – 1st expert on this subject based on the ideXlab platform
-
ISM – Image Content Annotation Based on Visual Features
Eighth IEEE International Symposium on Multimedia (ISM'06), 2006Co-Authors: Lei Ye, Philip Ogunbona, Jianqiang WangAbstract:Automatic image content annotation techniques attempt to explore structural visual features of images that describe image content and associate them with image semantics. In this paper, two types of Concept spaces, Atomic Concept and collective Concept spaces, are defined and the annotation problems in those spaces are formulated as feature classification and Bayesian inference, respectively. A scheme of image content annotation in this framework is presented and evaluated as an application of photo categorisation using MPEG-7 VCE2 dataset and its ground truth. The experimental results show a promising performance.
-
Image Content Annotation Based on Visual Features
Eighth IEEE International Symposium on Multimedia (ISM'06), 2006Co-Authors: Lei Ye, Philip Ogunbona, Jianqiang WangAbstract:Automatic image content annotation techniques attempt to explore structural visual features of images that describe image content and associate them with image semantics. In this paper, two types of Concept spaces, Atomic Concept and collective Concept spaces, are defined and the annotation problems in those spaces are formulated as feature classification and Bayesian inference, respectively. A scheme of image content annotation in this framework is presented and evaluated as an application of photo categorization using MPEG-7 VCE2 dataset and its ground truth. The experimental results show a promising performance
Lei Ye – 2nd expert on this subject based on the ideXlab platform
-
ISM – Image Content Annotation Based on Visual Features
Eighth IEEE International Symposium on Multimedia (ISM'06), 2006Co-Authors: Lei Ye, Philip Ogunbona, Jianqiang WangAbstract:Automatic image content annotation techniques attempt to explore structural visual features of images that describe image content and associate them with image semantics. In this paper, two types of Concept spaces, Atomic Concept and collective Concept spaces, are defined and the annotation problems in those spaces are formulated as feature classification and Bayesian inference, respectively. A scheme of image content annotation in this framework is presented and evaluated as an application of photo categorisation using MPEG-7 VCE2 dataset and its ground truth. The experimental results show a promising performance.
-
Image Content Annotation Based on Visual Features
Eighth IEEE International Symposium on Multimedia (ISM'06), 2006Co-Authors: Lei Ye, Philip Ogunbona, Jianqiang WangAbstract:Automatic image content annotation techniques attempt to explore structural visual features of images that describe image content and associate them with image semantics. In this paper, two types of Concept spaces, Atomic Concept and collective Concept spaces, are defined and the annotation problems in those spaces are formulated as feature classification and Bayesian inference, respectively. A scheme of image content annotation in this framework is presented and evaluated as an application of photo categorization using MPEG-7 VCE2 dataset and its ground truth. The experimental results show a promising performance
H. Arenas – 3rd expert on this subject based on the ideXlab platform
-
DEXA Workshops – Semantic matchmaking in geo service chains: reasoning with a location ontology
, 2004Co-Authors: R. Lemmens, H. ArenasAbstract:The growing demand for the discovery of geo Web services as parts of service chains necessitates semantic matchmaking between service descriptions. We propose a method for describing and matching services based on a geo location ontology and we demonstrate its power and its limitations with a simple user scenario. In a test environment using protege and the racer ontology reasoner we show some powerful constructs of Description Logics that allow us to distinguish different types of matches. We underline the importance of matching Atomic Concept conditions versus aggregated conditions. The use of OWL and OWL enabled tools prove to facilitate a powerful matchmaking environment.
-
Semantic matchmaking in geo service chains: reasoning with a location ontology
Proceedings. 15th International Workshop on Database and Expert Systems Applications 2004., 2004Co-Authors: R. Lemmens, H. ArenasAbstract:The growing demand for the discovery of geo Web services as parts of service chains necessitates semantic matchmaking between service descriptions. We propose a method for describing and matching services based on a geo location ontology and we demonstrate its power and its limitations with a simple user scenario. In a test environment using protege and the racer ontology reasoner we show some powerful constructs of Description Logics that allow us to distinguish different types of matches. We underline the importance of matching Atomic Concept conditions versus aggregated conditions. The use of OWL and OWL enabled tools prove to facilitate a powerful matchmaking environment.