The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, hetero...
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The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data. This paper describes how KOmF, the Khaos Ontology-based mediator Framework, is used to retrieve information and crystallize it in a (persistent) Knowledgebase. This information could be further analyzed later (by means of querying and reasoning). These kinds of systems (based on KOmF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a methodology for creating persistent and scalable knowledgebases from sets of OWL instances.
In various image processing tasks, enhancing resolution is a fundamental challenge, particularly along specific axes where resolution tends to be lower. This limitation can hinder the performance of models in tasks su...
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most of object detection algorithms do not yield perfect foreground segmentation masks. These errors in the initial stage of video surveillance systems could cause that the subsequent tasks like object tracking and be...
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The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a pano...
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In this paper, a new self-organizing neural gas model that we call Growing Hierarchical Bregman Neural Gas (GHBNG) has been proposed. Our proposal is based on the Growing Hierarchical Neural Gas (GHNG) in which Bregma...
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The construction of a model of the background of a scene still remains as a challenging task in video surveillance systems, in particular for moving cameras. This work presents a novel approach for constructing a pano...
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Self-organizing neural networks are usually focused on prototype learning, while the topology is held fixed during the learning process. Here we propose a method to adapt the topology of the network so that it reflect...
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There is a wide range of methods for lossy compression, but among those most used we find JPEG (Joint Photographic Experts Group) for still images. In this paper we present an intelligent system which is capable of re...
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In this paper a controller for PTZ cameras based on an unsupervised neural network model is presented. It takes advantage of the foreground mask generated by a non-parametric foreground detection subsystem. Thus, our ...
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most of the recommender systems are content-based: They provide the user a subset of items close to his interest by using the item features. In real recommender systems, the main problem is the big amount of items to ...
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