Hyperparameter Optimization for Image Recognition over an AR-Sandbox Based on Convolutional Neural Networks Applying a Previous Phase of Segmentation by Color–Space

Hyperparameter Optimization for Image Recognition over an AR-Sandbox Based on Convolutional Neural Networks Applying a Previous Phase of Segmentation by Color–Space

Immersive techniques such as augmented reality through devices such as the AR-Sandbox and deep learning through convolutional neural networks (CNN) provide an environment that is potentially applicable for motor rehabilitation and early education. However, given the orientation towards the creation...

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Bibliographic Details
Main Authors: Andrés Ovidio Restrepo Rodríguez, Daniel Esteban Casas Mateus, Paulo Alonso Gaona García, Carlos Enrique Montenegro Marín, Rubén González Crespo
Format: Article
Language:English
Published: MDPI AG 2018-12-01
Series:Symmetry
Subjects:
image acquisition
image processing
image recognition
convolutional neural network
dataset
loss function
accuracy
ROC curve
AR-Sandbox
random search
Online Access:https://www.mdpi.com/2073-8994/10/12/743

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https://www.mdpi.com/2073-8994/10/12/743

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