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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1276
Title: The application of liquid time-constant networks in learning handwashing process
Authors: Huynh Duc Khai 
Keywords: Liquid time-constant;Handwashing process;Recurrent neural network;Deep learning application
Issue Date: 2021
Publisher: Vietnamese-German University
Abstract: 
This thesis will introduce the core idea for making software that is able to detect whether a person has a qualified hand washing process or not by taking advantage of modern technology: Deep Learning. More specifically, by applying a new variation of Recurrent Neural Network (RNN) - the Liquid Time-constant (LTC) Network - the software now can have more accurate in classifying an entire handwashing process compared to
vanilla RNN algorithm of its - the famous Long Short Term Memory (LSTM) networks. In this paper, I take one step further by creating multiple LTC networks, combine them into a decision forest and add one more layer outside to determine which recorded video is a qualified hand washing process. Although LTC improves effectiveness, we still need more consideration to compare it to more recent advanced variations of neuron
networks to understand more about its strength and weakness.
URI(1): http://epub.vgu.edu.vn/handle/dlibvgu/1276
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)

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