Search Results - "Crăciun, Marian Viorel" :: K.UTB vyhledávací portál

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Clinical Study and Microbiological Analysis of Periodontopathogenic Microflora Analyzed among Children and Adolescents with Cardiovascular Diseases Compared to Group with Good General Status

by Chipirliu, Oana, Crăciun, Marian Viorel, Matei, Madalina Nicoleta
Published in Pediatric reports (18.06.2024)

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Preliminary Experiments of a Real-World Authentication Mechanism Based on Facial Recognition and Fully Homomorphic Encryption

by Crihan, Georgiana, Dumitriu, Luminița, Crăciun, Marian Viorel
Published in Applied sciences (01.01.2024)

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Comparative Clinical Study on Periodontal Health Status and Early Diagnosis of Periodontal Diseases Quantified through Clinical Periodontal Indices on a Group of Children and Adolescents with and without Cardiovascular Diseases

by Chipirliu, Oana, Crăciun, Marian Viorel, Matei, Madalina Nicoleta
Published in Pediatric reports (26.12.2023)

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Learning the Structure of Bayesian Network from Small Amount of Data

by Bogdan COCU, Marian Viorel CRACIUN, Adina COCU
Published in Analele Universităţii "Dunărea de Jos" Galaţi: Fascicula III, Electrotehnică, Electronică, Automatică, Informatică (01.12.2009)

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Combining Unsupervised and Supervised Artificial Neural Networks to PredictAquatic Toxicity

by Gini, Giuseppina, Craciun, Marian Viorel, König, Christoph, Benfenati, Emilio
Published in Journal of Chemical Information and Computer Sciences (01.11.2004)

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Journal Article

Clinical Study and Microbiological Analysis of Periodontopathogenic Microflora Analyzed among Children and Adolescents with Cardiovascular Diseases Compared to Group with Good General Status

Preliminary Experiments of a Real-World Authentication Mechanism Based on Facial Recognition and Fully Homomorphic Encryption

Comparative Clinical Study on Periodontal Health Status and Early Diagnosis of Periodontal Diseases Quantified through Clinical Periodontal Indices on a Group of Children and Adolescents with and without Cardiovascular Diseases

Learning the Structure of Bayesian Network from Small Amount of Data

Combining Unsupervised and Supervised Artificial Neural Networks to PredictAquatic Toxicity

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