Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder”
Presents corrections to the above mentioned paper.
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Online Access: | https://ieeexplore.ieee.org/document/9130173/ |
| _version_ | 1819295727306670080 |
|---|---|
| author | Tingting Chen Xueping Liu Bizhong Xia Wei Wang Yongzhi Lai |
| author_facet | Tingting Chen Xueping Liu Bizhong Xia Wei Wang Yongzhi Lai |
| author_sort | Tingting Chen |
| collection | DOAJ |
| description | Presents corrections to the above mentioned paper. |
| first_indexed | 2024-12-24T04:46:49Z |
| format | Article |
| id | doaj.art-56acebcfe27b44a090f80b57593283fe |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-24T04:46:49Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-56acebcfe27b44a090f80b57593283fe2022-12-21T17:14:40ZengIEEEIEEE Access2169-35362020-01-01811706211706210.1109/ACCESS.2020.30040989130173Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder”Tingting Chen0Xueping Liu1Bizhong Xia2Wei Wang3Yongzhi Lai4Graduate School at Shenzhen, Tsinghua University, Shenzhen, ChinaGraduate School at Shenzhen, Tsinghua University, Shenzhen, ChinaGraduate School at Shenzhen, Tsinghua University, Shenzhen, ChinaSunwoda Electronic Company, Shenzhen, Ltd., ChinaSunwoda Electronic Company, Shenzhen, Ltd., ChinaPresents corrections to the above mentioned paper.https://ieeexplore.ieee.org/document/9130173/ |
| spellingShingle | Tingting Chen Xueping Liu Bizhong Xia Wei Wang Yongzhi Lai Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” IEEE Access |
| title | Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” |
| title_full | Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” |
| title_fullStr | Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” |
| title_full_unstemmed | Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” |
| title_short | Corrections to “Unsupervised Anomaly Detection of Industrial Robots Using Sliding-Window Convolutional Variational Autoencoder” |
| title_sort | corrections to x201c unsupervised anomaly detection of industrial robots using sliding window convolutional variational autoencoder x201d |
| url | https://ieeexplore.ieee.org/document/9130173/ |
| work_keys_str_mv | AT tingtingchen correctionstox201cunsupervisedanomalydetectionofindustrialrobotsusingslidingwindowconvolutionalvariationalautoencoderx201d AT xuepingliu correctionstox201cunsupervisedanomalydetectionofindustrialrobotsusingslidingwindowconvolutionalvariationalautoencoderx201d AT bizhongxia correctionstox201cunsupervisedanomalydetectionofindustrialrobotsusingslidingwindowconvolutionalvariationalautoencoderx201d AT weiwang correctionstox201cunsupervisedanomalydetectionofindustrialrobotsusingslidingwindowconvolutionalvariationalautoencoderx201d AT yongzhilai correctionstox201cunsupervisedanomalydetectionofindustrialrobotsusingslidingwindowconvolutionalvariationalautoencoderx201d |