Please use this identifier to cite or link to this item:
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
Keywords: object detection
object counting
convolutional neuronal networks
machine learning
Issue Date: Jan-2019
Publisher: Universitat Oberta de Catalunya (UOC)
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.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

Files in This Item:
File Description SizeFormat 
aarencTFM0119memoria.pdfMemoria del TFM2.81 MBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons