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A Deep Adversarial Approach Based on Multi-Sensor Fusion for Semi-Supervised Remaining Useful Life Prognostics
(MDPI, 2020)
Multi-sensor systems are proliferating in the asset management industry. Industry 4.0, combined with the Internet of Things (IoT), has ushered in the requirements of prognostics and health management systems to predict the ...
Instance-based defense against adversarial attacks in Deep Reinforcement Learning
Deep Reinforcement Learning systems are now a hot topic in Machine Learning for their effectiveness in many complex tasks, but their application in safety-critical domains (e.g., robot control or self-autonomous driving) ...
La transformación de la cultura organizacional del fuero penal santafesino, durante el proceso de cambio hacia un sistema adversarial
(2018-09-05)
En este estudio se describe el proceso de reforma del sistema procesal penal que introdujo la provincia de Santa Fe a partir del 10 de febrero de 2014. Se identifican los principales cambios organizacionales que se ...
Recongnizing the limits of the right to counsel as a guarantee of justice
(Escuela de Derecho - Universidad Viña del Mar, 2014)
This paper examines the role of the right to counsel in criminal cases as a structural,
theoretical, and actual guarantee of justice. It compares the scope and history of the
right to counsel in the United States and ...
O sistema acusatório e o projeto de novo Código de Processo Penal: uma reflexão sobre a (in)conformidade constitucional
(Universidade Federal de Santa MariaBrasilUFSMCentro de Ciências Sociais e Humanas, 2014-12-04)
The main objective of this research was to identify the points set out in the Project of the new Code of Criminal Procedure (PL 8045/2010) that are inconsistent with the provisions of the criminal procedure system adopted ...
Plantar pressure image classification employing residual-network model-based conditional generative adversarial networks: a comparison of normal, planus, and talipes equinovarus feet
The number of deep learning (DL) layers increases, and following the performance of computing nodes improvement, the output accuracy of deep neural networks (DNN) faces a bottleneck problem. The resident network (RN) based ...