Unsupervised Anomaly Detection Approach for Shift Quality Assessment Using Deep Neural Networks-Reference-Cited by-同舟云学术

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Unsupervised Anomaly Detection Approach for Shift Quality Assessment Using Deep Neural Networks

Published:2022-06-05 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Intelligent Vehicles Symposium (IV)
language:
Short-container-title:

Author:

Oh Geesung¹,Park Joonghoo¹,Hwang Kyunghun²,Lim Sejoon³

Affiliation:

1. Kookmin University,Graduate School of Automotive Engineering,Seoul,Korea

2. Hyundai Motor Group,Electrification Energy Efficiency & Drivability Test 3 Team,Hwaseong,Korea

3. Kookmin University,College of Automotive Engineering,Department of Automobile and IT Convergence,Seoul,Korea

Funder

Hyundai Motor Group

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9826996/9826997/09827200.pdf?arnumber=9827200

Reference18 articles.

1. A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data

2. Unsupervised Anomaly Detection Approach for Time-Series in Multi-Domains Using Deep Reconstruction Error

3. Lstm-based encoder-decoder for multi-sensor anomaly detection;malhotra;arXiv preprint arXiv 1607 00148,2016

4. Memorizing Normality to Detect Anomaly: Memory-Augmented Deep Autoencoder for Unsupervised Anomaly Detection

5. CANnolo: An Anomaly Detection System Based on LSTM Autoencoders for Controller Area Network

Cited by 4 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. Intelligent Car Cockpit Comfort Evaluation Model Based on SVM;IEEE Access;2024

2. Shift Quality Classifier Using Deep Neural Networks on Small Data with Dropout and Semi-Supervised Learning;IEICE Transactions on Information and Systems;2023-12-01

3. Research on Control Quality Evaluation System of Static Shift for a Hydraulic Mechanical Transmission;2023 4th International Conference on Computer Engineering and Intelligent Control (ICCEIC);2023-10-20

4. Study on the Influence of Machining Deviation of Vehicle Automatic Transmission Shifting Control Components on Calibration Parameters;Journal of Physics: Conference Series;2023-10-01

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