972 resultados para Automatic Image Annotation


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A dissertação em apreço resultou da necessidade em otimizar os recursos técnicos, mas sobretudo humanos, afetos às verificações de instrumentos de medição, no âmbito do Controlo Metrológico Legal. Estas verificações, realizadas nos termos do cumprimento das competências outrora atribuídas à Direção de Serviços da Qualidade da então Direção Regional da Economia do Norte, eram operacionalizadas pela Divisão da Qualidade e Licenciamento, na altura dirigida pelo subscritor da presente tese, nomeadamente no que respeita aos ensaios efetuados, em laboratório, a manómetros analógicos. O objetivo principal do trabalho foi alcançado mediante o desenvolvimento de um automatismo, materializado pela construção de um protótipo, cuja aplicação ao comparador de pressão múltiplo, dantes em utilização, permitiria realizar a leitura da indicação de cada manómetro analógico através de técnicas de processamento de imagem, função esta tradicionalmente efetuada manualmente por um operador especializado. As metodologias de comando, controlo e medição desse automatismo foram realizadas através de um algoritmo implementado no software LabVIEW® da National Intruments, particularmente no que respeita ao referido processamento das imagens adquiridas por uma câmara de vídeo USB. A interface com o hardware foi concretizada recorrendo a um módulo de Aquisição de Dados Multifuncional (DAQ) USB-6212, do mesmo fabricante. Para o posicionamento horizontal e vertical da câmara de vídeo USB, recorreu-se a guias lineares acionadas por motores de passo, sendo que estes dispositivos foram igualmente empregues no acionamento do comparador de pressão. Por último, procedeu-se à aquisição digital da leitura do padrão, recorrendo à respetiva virtualização, bem como a uma aplicação desenvolvida neste projeto, designada appMAN, destinada à gestão global do referido automatismo, nomeadamente no que se refere ao cálculo do resultado da medição, erro e incerteza associada, e emissão dos respetivos documentos comprovativos.

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BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Dissertação para obtenção do Grau de Mestre em Engenharia Mecânica

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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Research Project submited as partial fulfilment for the Master Degree in Statistics and Information Management

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

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The dissertation presented for obtaining the Master’s Degree in Electrical Engineering and Computer Science, at Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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This paper incorporates egocentric comparisons into a human capital accumulation model and studies the evolution of positive self image over time. The paper shows that the process of human capital accumulation together with egocentric comparisons imply that positive self image of a cohort is first increasing and then decreasing over time. Additionally, the paper finds that positive self image: (1) peaks earlier in activities where skill depreciation is higher, (2) is smaller in activities where the distribution of income is more dispersed, (3) is not a stable characteristic of an individual, and (4) is higher for more patient individuals.

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

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This paper investigates the implications of individuals’ mistaken beliefs of their abilities on incentives in organizations using the principal-agent model of moral hazard. The paper shows that if effort is observable, then an agent’s mistaken beliefs about own ability are always favorable to the principal. However, if effort is unobservable, then an agent’s mistaken beliefs about own ability can be either favorable or unfavorable to the principal. The paper provides conditions under which an agent’s over estimation about own ability is favorable to the principal when effort is unobservable. Finally, the paper shows that workers’ mistaken beliefs about their coworkers’ abilities make interdependent incentive schemes more attractive to firms than individualistic incentive schemes.

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This paper analyzes the implications of worker overestimation of productivity for firms in which incentives take the form of tournaments. Each worker overestimates his productivity but is aware of the bias in his opponent’s self-assessment. The manager of the firm, on the other hand, correctly assesses workers’ productivities and self-beliefs when setting tournament prizes. The paper shows that, under a variety of circumstances, firms make higher profits when workers have positive self-image than if workers do not. By contrast, workers’ welfare declines due to their own misguided choices.