APPLICATION OF RECURRENT NEURAL NETWORK ALGORITHM WITH LSTM ARCHITECTURE TO DETECT VIOLATIONS ON SOCIAL DISTANCING
The COVID-19 pandemic which began at the end of 2019 is still plaguing the world even now. The pandemic which caused by the Novel Coronavirus-19 has had an impact on various sectors around the world. According to WHO, this virus can spread through droplets that forms when an infected person cough...
Saved in:
Main Author: | Tri Farhan, Afif |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/63737 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
Short-term residential load forecasting based on LSTM recurrent neural network
by: Kong, Weicong, et al.
Published: (2021) -
HARDWARE DESIGN AND IMPLEMENTATION FOR BLUETOOTH LOCALIZATION BASED SOCIAL DISTANCING VIOLATION DETECTION
by: Husni, Faizal -
Automated traffic violation apprehension system using genetic algorithm and artificial neural network
by: Uy, Aaron Christian P., et al.
Published: (2017) -
A training algorithm and stability analysis for recurrent neural networks
by: Xu, Zhao, et al.
Published: (2014) -
Recurrent neural networks: A constructive algorithm, and its properties
by: Tsoia, A.C., et al.
Published: (2014)