Programa
12.00 horas
Deep Detection and Segmentation Models for Plant Physiology and Precision Agriculture
Ángela Casado García
Grupo PSYCOTRIP
Universidad de La Rioja
Descripción
In this thesis, we have focused on developing methods to improve the performance of deep object detection models. To achieve such a goal, we have used ensemble methods to devise an algorithm that enhances the accuracy and robustness of object detection models. Moreover, the proposed algorithm is the basis for defining semi-supervised learning techniques that reduce the number of annotated images that are required to train object detection models. In addition, we have simplified the creation and use of detection models by building an easy-to-use graphical interface. The developed methods and tools are not only applicable to object detection problems, but we have generalised them to a different computer vision task that is semantic segmentation. Finally, our work is not only theoretical, but it has also been applied to tackle actual problems in plant physiology and precision agriculture.
Listado de charlas del Seminario Mirian Andrés
Mirian Andrés (1979-2008) fue compañera y participante en este Seminario durante el tiempo que trabajó en la Universidad de La Rioja.
Para quién
Público en general.
Entrada libre hasta completar el aforo.
Dirección
Jesús María Aransay Azofra
Departamento de Matemáticas y Computación
Universidad de La Rioja
jesus-maria.aransay@unirioja.es
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