The DOI matches its Crossref record; 37 of the 37 references it cites were found in a registry or an index.
Fault diagnosis for small samples based on attention mechanism
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Citations
Cites
Zhang, W., Peng, G., Li, C., Chen, Y., & Zhang, Z. (2017) · Sensors · doi:10.3390/s17020425 · Cited by 1,925
Pre-trained models for natural language processing: A survey
Qiu, X., Sun, T., Xu, Y., Shao, Y., Dai, N., & Huang, X. (2020) · Science China Technological Sciences · doi:10.1007/s11431-020-1647-3 · Cited by 1,591
Deep Learning Algorithms for Bearing Fault Diagnostics—A Comprehensive Review
Zhang, S., Zhang, S., Wang, B., & Habetler, T. G. (2020) · IEEE Access · doi:10.1109/access.2020.2972859 · Cited by 913
Bearing fault diagnosis base on multi-scale CNN and LSTM model
Chen, X., Zhang, B., & Gao, D. (2021) · Journal of Intelligent Manufacturing · doi:10.1007/s10845-020-01600-2 · Cited by 739
Zhao, Z., Li, T., Wu, J., Sun, C., Wang, S., Yan, R., & Chen, X. (2020) · ISA Transactions · doi:10.1016/j.isatra.2020.08.010 · Cited by 688
Bearing fault diagnosis based on vibro-acoustic data fusion and 1D-CNN network
Wang, X., Mao, D., & Li, X. (2021) · Measurement · doi:10.1016/j.measurement.2020.108518 · Cited by 641
Adaptive batch normalization for practical domain adaptation
Li, Y., Wang, N., Shi, J., Hou, X., & Liu, J. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.03.005 · Cited by 601
A Brief Survey on Semantic Segmentation with Deep Learning
Hao, S., Zhou, Y., & Guo, Y. (2020) · Neurocomputing · doi:10.1016/j.neucom.2019.11.118 · Cited by 596
Recent advances in small object detection based on deep learning: A review
Tong, K., Wu, Y., & Zhou, F. (2020) · Image and Vision Computing · doi:10.1016/j.imavis.2020.103910 · Cited by 592
Performance Evaluation of Deep Neural Networks Applied to Speech Recognition: RNN, LSTM and GRU
Shewalkar, A., Nyavanandi, D., & Ludwig, S. A. (2019) · Journal of Artificial Intelligence and Soft Computing Research · doi:10.2478/jaiscr-2019-0006 · Cited by 576
Metadata
- Authors
- Zhang, X., He, C., Lu, Y., Chen, B., Zhu, L., & Zhang, L.
- Venue
- Measurement
- Publisher
- Elsevier BV
- Published
- 2022-01
- Volume
- 187
- Pages
- 110242
- ISSN
- 0263-2241 (ISSN-L)
- OpenAlex
- W3203494009
- Cited by
- 299
- References
- 37
- FWCI
- 14.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Fault diagnosis for small samples based on attention mechanism. https://app.cochat.ai/papers/10.1016/j.measurement.2021.110242
- The paper
- Zhang, X., He, C., Lu, Y., Chen, B., Zhu, L., & Zhang, L. (2022). Fault diagnosis for small samples based on attention mechanism. Measurement. https://doi.org/10.1016/j.measurement.2021.110242
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
