In diesem Beitrag wird ein System zur zweidimensionalen Segmentierung subkortikaler Regionen vorgestellt. Erste Ergebnisse werden anhand von realen Schichtbilddaten und Phantomen präsentiert und eine Erweiterung ...
ISBN:
(数字)9783540264316
ISBN:
(纸本)3540250522
In diesem Beitrag wird ein System zur zweidimensionalen Segmentierung subkortikaler Regionen vorgestellt. Erste Ergebnisse werden anhand von realen Schichtbilddaten und Phantomen präsentiert und eine Erweiterung des Modells auf ein 3D-Verfahren diskutiert. Das sequentiell arbeitende Verfahren verwendet eine Gewebeklassifikation und gradientenvektorflussbasierte aktive Konturmodelle, um den Bildraum bezüglich der gesuchten Strukturen zu partitionieren und diese dann zu segmentieren.
A literature review is an essential part of research. Beginning researchers who would like to conduct research in any field commonly review previous papers to identify trends and gaps in research. However, conducting ...
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Bed load transport is a longstanding problem despite its major implication in river morphodynamics. The physical processes ruling coarse-particle/fluid systems are indeed poorly known, impairing our ability to compute...
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ISBN:
(纸本)9780415453639
Bed load transport is a longstanding problem despite its major implication in river morphodynamics. The physical processes ruling coarse-particle/fluid systems are indeed poorly known, impairing our ability to compute local and even bulk quantities such as the sediment flux in rivers. We present an experimental study of a two-size mixture of coarse spherical glass beads entrained by a shallow turbulent water flow down a steep channel with a mobile bed. The particle diameters were 4 and 6 mm, the channel width 6.5 mm and the channel inclination 12.5%. The water flow rate and the solid discharge were kept constant at the upstream entrance. They were adjusted to obtain bed load equilibrium, that is, neither bed degradation nor aggradation over sufficiently long time intervals. Flows were filmed from the side by a high-speed camera. Using imageprocessingalgorithms made it possible to determine the position, velocity and trajectory of each spherical particle thanks to a PTV algorithm (particle tracking velocimetry). Transitions of the state of motion (rest, rolling or saltating) and flow depth were also determined. New data were compared to previous results obtained with spherical particles of uniform size. They confirm that the free surface acting as a physical barrier by truncating the saltation trajectories is very important on steep slopes. The use of a two-size mixture with the 4 turn beads tending to be blocked in the 6.5 mm wide channel resulted in a bed mainly formed by these 4 mm beads. This particular structure explained the single peak vertical distribution of the solid discharge contrary to the uniform case where several peaks corresponding to rolling were observed.
Studying circumstellar environments is crucial for understanding exoplanets and stellar systems. Instruments like SPHERE can extract information about these environments by leveraging advanced image reconstruction met...
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ISBN:
(数字)9789464593617
ISBN:
(纸本)9798331519773
Studying circumstellar environments is crucial for understanding exoplanets and stellar systems. Instruments like SPHERE can extract information about these environments by leveraging advanced image reconstruction methods, possibly based on deep learning. This work focuses on unfolded proximal neural networks based on Condat- vii iterations and proposes a new nonlinear formulation. To evaluate and compare the performance of the proposed reconstruction strategies, two datasets dedicated to circumstellar environments analysis in the context of high-contrast imagery have been created offering different level of complexity in the evaluation of the performance.
This predoctoral research project is carried out in the framework of an international co-tutelage between the University of Jaén and the Universidad Autónoma de Occidente in Cali, Colombia with the participa...
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ISBN:
(数字)9798350364538
ISBN:
(纸本)9798350364545
This predoctoral research project is carried out in the framework of an international co-tutelage between the University of Jaén and the Universidad Autónoma de Occidente in Cali, Colombia with the participation of the CyTI Department of the Universidad de San Buenaventura. Its main objective is to systematize the processes of maintenance and diagnosis of modules in Photovoltaic systems (PVS) using computational tools based on Artificial Intelligence (AI). The project seeks to reduce operating costs, minimize human errors and detect possible failures early, in order to extend the operating hours of the PV systems and reduce the time spent on preventive maintenance. To achieve these objectives, deep learning algorithms are used in infrared (IR) imageprocessing. These algorithms make it possible to evaluate the state of the photovoltaic modules by analyzing variations in surface temperatures, detecting anomalous situations and failures in each photovoltaic (PV) collector module. The implementation of these techniques will contribute to the development of effective methodologies that will significantly improve PV maintenance. This advance represents significant progress in the efficiency and sustainability of solar photovoltaic energy, with applications of great relevance in both the scientific and technological *** proyecto de investigación predoctoral se lleva a cabo en el marco de una cotutela internacional entre la Universidad de Jaén y la Universidad Autónoma de Occidente en Cali, Colombia con la participación del Departamento de CyTI de la Universidad de San Buenaventura. Su objetivo principal es sistematizar los procesos de mantenimiento y diagnóstico de módulos en Sistemas Fotovoltaicos (SFV) mediante el uso de herramientas computacionales basadas en Inteligencia Artificial (IA). El proyecto busca reducir costos operativos, minimizar errores humanos y detectar tempranamente posibles fallos, con el fin de prolongar las horas de funcionamiento de los SFV
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