CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE FOR HAND GESTURE RECOGNITION

被引：0
|
作者：
Pinzon Arenas, Javier Orlando [1 ]
Useche Murillo, Paula Catalina [1 ]
Jimenez Moreno, Robinson [1 ]
机构：
[1] Nueva Granada Mil Univ, Fac Engn, Bogota, Colombia
来源：
PROCEEDINGS OF THE 2017 IEEE XXIV INTERNATIONAL CONFERENCE ON ELECTRONICS, ELECTRICAL ENGINEERING AND COMPUTING (INTERCON) | 2017年
关键词：
Convolutional Neural Network; Validation Error; Accuracy; Hand Gesture;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
This paper presents the design of a convolutional neural network architecture using the MatConvNet library for MATLAB in order to achieve the recognition of 2 classes of hand gestures: "open" and "closed". Six architectures were implemented to which their hyperparameters and depth were varied to observe their behavior through the validation error in the training and accuracy in the estimation of each one of the set classes, which was evaluated by a matrix of confusion. Given each of these results, the neural network with the best performance was chosen.
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页数：4
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