Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/88005
Title: Estudio de viabilidad para el control de existencias mediante reconocimiento visual y redes neuronales convolucionales
Author: Arencibia Guerra, Antonio
Director: Casas-Roma, Jordi  
Tutor: Hernández-González, Jerónimo  
Abstract: This project investigates the viability of a stock control system for a limited range of fruit in a three-dimensional, controlled environment. The system is based on deep learning techniques with the application of convolutional neural networks being used to detect objects in images.
Keywords: object detection
object counting
convolutional neuronal networks
machine learning
Document type: info:eu-repo/semantics/masterThesis
Issue Date: Jan-2019
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/  
Appears in Collections:Bachelor thesis, research projects, etc.

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