Fault Detection in Railway Tracks Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Fault Detection in Railway Tracks Using Artificial Neural Networks

Published:2018-08 Issue: Volume: Page:
ISSN:
Container-title:2018 International Conference on Research in Intelligent and Computing in Engineering (RICE)
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Author:

Welankiwar Aalhad,Sherekar Shubham,Bhagat Amol P.,Khodke Priti A.

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8488872/8509031/08509083.pdf?arnumber=8509083

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. ECARRNet: An Efficient LSTM-Based Ensembled Deep Neural Network Architecture for Railway Fault Detection;AI;2024-04-08

2. Railway Accident Reduction By Passenger Detection Using Machine Learning Techniques;2024 IEEE 9th International Conference for Convergence in Technology (I2CT);2024-04-05

3. Multiclass Classification of Rail Track Defects Using Deep Learning Techniques;2023 International Conference on Smart Systems for applications in Electrical Sciences (ICSSES);2023-07-07

4. Prediction of rail-wheel contact parameters for a metro coach using machine learning;Expert Systems with Applications;2023-04

5. Railway Track Fault Detection using Deep Neural Networks;2022 IEEE 6th Conference on Information and Communication Technology (CICT);2022-11-18

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