Randomized neural network based signature for dynamic texture classification
作者：
Highlights：
• In this study, we model a dynamic texture as a randomized neural network.
• A randomized neural network is a feed forward neural network with a single-hidden layer.
• Slices of the dynamic textures are divided into windows to build a training dataset.
• Each window provides an input feature vector and corresponding label.
• The weights of the output neuron layer are the dynamic texture descriptors.
摘要
•In this study, we model a dynamic texture as a randomized neural network.•A randomized neural network is a feed forward neural network with a single-hidden layer.•Slices of the dynamic textures are divided into windows to build a training dataset.•Each window provides an input feature vector and corresponding label.•The weights of the output neuron layer are the dynamic texture descriptors.
论文关键词：Dynamic textures,Randomized neural network,Dynamic texture analysis method
论文评审过程：Received 18 December 2018, Revised 19 April 2019, Accepted 30 May 2019, Available online 30 May 2019, Version of Record 14 June 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.05.055
