Mostrando 561 - 580 Resultados de 1,125 Para Buscar 'Deep house', tiempo de consulta: 0.18s Limitar resultados
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    por Schirmer, Pascal A., Mporas, Iosif
    Publicado 2022
    “…The aim of Non-Intrusive Load Monitoring is to estimate the energy consumption of individual electrical appliances by disaggregating the overall power consumption that has been sampled from a smart meter at a house or commercial/industrial building. Last decade’s developments in deep learning and the utilization of Convolutional Neural Networks have improved disaggregation accuracy significantly, especially when utilizing two-dimensional signal representations. …”
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    “…Purpose: To assess image quality and uncertainty in organ-at-risk segmentation on cone beam computed tomography (CBCT) enhanced by deep-learning convolutional neural network (DCNN) for head and neck cancer. …”
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    “…Our proposed approach showed the success of a weakly supervised deep learning approach in MRI brain extraction even in the presence of pathology. …”
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    “…Methods: A SORS imaging system was built in-house. Proof of concept SORS imaging was achieved using a PTFE-skull-tissue phantom. …”
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    “…This potentially allows for dose‐escalation to deep‐seated masses to debulk unresectable large tumors providing an option for neoadjuvant treatment. …”
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    “…Because of inherent redundancies in HSI and in order to facilitate the use of deep‐learning models, dimension reduction is a common preprocessing step. …”
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    “…METHODS: We have tested a standardised phenotyping method termed ‘Phenomodels’ for integrating deep‐phenotyping information with our in‐house developed clinical whole exome/genome sequencing analytical pipeline. …”
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