A systematic literature review of deep learning neural network for time series air quality forecasting

2021 ◽  
Author(s):  
Nur’atiah Zaini ◽  
Lee Woen Ean ◽  
Ali Najah Ahmed ◽  
Marlinda Abdul Malek
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Deep Learning ◽  
Air Quality ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Deep Learning Neural Network ◽  
Air Quality Forecasting

Time Series in Sensor Data Using State-of-the-Art Deep Learning Approaches: A Systematic Literature Review

2021 ◽  
pp. 503-514
Author(s):  
Luis-Roberto Jácome-Galarza ◽  
Miguel-Andrés Realpe-Robalino ◽  
Jonathan Paillacho-Corredores ◽  
José-Leonardo Benavides-Maldonado
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Literature Review ◽  
Systematic Literature Review ◽  
State Of The Art ◽  
Sensor Data ◽  
Learning Approaches

Deep Learning Neural Network for Time Series Water Level Forecasting

2021 ◽  
pp. 22-29
Author(s):  
Nuratiah Zaini ◽  
Marlinda Abdul Malek ◽  
Shuhairy Norhisham ◽  
Nurul Hani Mardi
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Deep Learning ◽  
Water Level ◽  
Deep Learning Neural Network

scholarly journals Augmented Reality Maintenance Assistant Using YOLOv5

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
Real Time ◽  
Recognition System ◽  
High Accuracy ◽  
Video Streams ◽  
The Neural Network ◽  
Deep Learning Neural Network

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.

scholarly journals Modeling the heat resistance of nickel-based superalloys by a deep learning neural network

2020 ◽  
Author(s):  
Dmitry A. Tarasov ◽  
Andrey G. Tyagunov ◽  
Oleg B. Milder
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Heat Resistance ◽  
Deep Learning Neural Network
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