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ABC - Mintransporte 5 ¿Cómo se normaliza el registro inicial de los vehículos de carga para los cuáles se expidió con posterioridad a la matrícula, el Certificado de Cumplimiento de Requisitos-CCR o la Aprobación de Caución-CC ?
GenTron: Diffusion Transformers for Image and Video Generation Abstract In this study, we explore Transformer-based diffusion models for image and video generation Despite the domi-nance of Transformer architectures in various fields due to their flexibility and scalability, the visual generative domain primarily utilizes CNN-based U-Net architectures, particu-larly in diffusion-based models We introduce GenTron, a family of Generative models employing
Normalized Hurricane Damage in the United States: 1900–2005 Abstract: After more than two decades of relatively little Atlantic hurricane activity, the past decade saw heightened hurricane activity and more than $150 billion in damage in 2004 and 2005 This paper normalizes mainland U S hurricane damage from 1900–2005 to 2005 values using two methodologies A normalization provides an estimate of the damage that would occur if storms from the past
DOMAIN GENERALIZATION ON EFFICIENT ACOUSTIC SCENE . . . ABSTRACT It is a practical research topic how to deal with multi-device audio inputs by a single acoustic scene classification system with efficient design In this work, we propose Residual Normaliza-tion, a novel feature normalization method that uses frequency-wise normalization with a shortcut path to discard unnecessary device-specific information without losing useful information for
Relatório e Contas Nas secções seguintes caracterizam-se as iniciativas realizadas em 2007, começando por apresentar aquelas que são tidas como mais estru- turantes ou de maior impacto potencial, em alguns casos agrupando-as pela sua afi nidade (as referências relativas às secções onde são analisa- das foram incluídas na Figura 1)
Deep learning for World Health Organization grades of . . . Purpose The World Health Organization (WHO) grading system of pancreatic neuroendocrine tumor (PNET) plays an important role in the clinical decision The rarity of PNET often negatively afects the radiological application of deep learn-ing algorithms due to the low availability of radiological images We tried to investigate the feasibility of predicting WHO grades of PNET on contrast