Análisis de algoritmos de detección de objetos para la creación de un prototipo basado en la fusión de dos modelos de reconocimiento
DOI:
https://doi.org/10.29018/issn.2588-1000vol3iss20.2019pp5-10Palabras clave:
RPN. FRUSTUN, KITTI, LIDAR, CNNResumen
En el presente estudio se muestra una metodología experimental deductiva basada en redes neuronales para el reconocimiento de objetos con el uso de CNN. Nuestro objetivo es generar un prototipo el cual está basado en un mapa de características en combinación con RPN y propuesta de recorte en tronco que usa TNET para la detección 3D, dado por modelos de reconocimiento de objetos de la plataforma KITTI ,enfocados especialmente en AVOD y FPOINTNET, obteniendo una mayor precisión en objetos más pequeños que fácilmente son descartables por la nube de puntos proporcionados por el sensor laser 3d LIDAR HDL-64 pero no por el mapeado de características.
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