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This work addresses the development of a unified approach to content-based indexing and retrieval of digital videos from television archives. The proposed approach has been designed to deal with arbitrary television genres, making it suitable for various applications. To achieve this goal, the main steps of a content-based video retrieval system are(More)
This paper presents a novel multimedia information system, called SAPTE, for supporting the discourse analysis and information retrieval of television programs from their corresponding video recordings. Unlike most common systems, SAPTE uses both content independent and dependent metadata, which are determined by the application of discourse analysis(More)
This paper describes the development of a multimedia information system to support the discourse analysis of video recordings of television programs. Although the TV system is one of the most fascinating media phenomena ever created by men, there is still a lack of information systems that allow an effective retrieval of TV information relevant to the(More)
—This work addresses the problem of automated visual inspection of surface defects on rolled steel, by using Computer Vision and Artificial Neural Networks. In recent years, the increasing throughput in the steel industry has become the visual inspection a critical production bottleneck. In this scenario, to assure a high rolled steel quality, novel(More)
This paper presents the design and development of a new plug-in to the well-known MIPS Assembler and Runtime Simulator (MARS). The MIPS processor is a reduced instruction set computer (RISC), while the MARS simulator is a lightweight interactive development environment for programming in MIPS assembly language, intended for educational-level use. The(More)
This paper presents a multimodal approach to perform content-based sentiment analysis in TV newscasts videos in order to assist in the automatic estimation of polarity tension of TV news. The proposed approach aims to contribute to the semiodiscoursive study relative to the construction of ethos of those TV shows. In order to achieve this goal, it is(More)
    This work addresses the development of an automated visual inspection system for rolled steel defects detection, by using Computer Vision techniques and Artificial Neural Networks. Unlike most common techniques, which are frequently based on manual estimations that lead to significant time and financial constraints, it presents an automatic system(More)
– This paper describes an application for rolled steel defect classification using SOM (Self-Organizing Maps) neural networks and the non-parametric method k-NN (k-Nearest Neighbors). This strategy was applied to classify wave-form defect in images extracted from real-world video streams realized in a steelmaking cold rolled mill line. The interested object(More)
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