HGR‐Net: a fusion network for hand gesture segmentation and recognition

HGR‐Net: a fusion network for hand gesture segmentation and recognition

We propose a two‐stage convolutional neural network (CNN) architecture for robust recognition of hand gestures, called HGR‐Net, where the first stage performs accurate semantic segmentation to determine hand regions, and the second stage identifies the gesture. The segmentation stage architecture is...

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Bibliographic Details
Main Authors: Amirhossein Dadashzadeh, Alireza Tavakoli Targhi, Maryam Tahmasbi, Majid Mirmehdi
Format: Article
Language:English
Published: Wiley 2019-12-01
Series:IET Computer Vision
Subjects:
fusion network
hand gesture segmentation
robust recognition
real-world applications
cluttered backgrounds
unconstrained environmental factors
Online Access:https://doi.org/10.1049/iet-cvi.2018.5796

Internet

https://doi.org/10.1049/iet-cvi.2018.5796

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