A Benchmarking Model based on Research Performance Indicators of Engineering Institutions: A Principal Component Analysis
Author:
Affiliation:
1. Information and Library Network Centre, India
2. P G Dept. of Computer Sci. and Technology, Sardar Patel University, India
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3590837.3590911
Reference16 articles.
1. Basak , H. 2021. Cervical Cytology Classification Using PCA and GWO Enhanced Deep Features Selection. SN Computer Science. 2, 5 ( 2021 ). DOI: https://doi.org/10.1007/s42979-021-00741-2. 10.1007/s42979-021-00741-2 Basak, H. 2021. Cervical Cytology Classification Using PCA and GWO Enhanced Deep Features Selection. SN Computer Science. 2, 5 (2021). DOI: https://doi.org/10.1007/s42979-021-00741-2.
2. Dimensionality Reduction of Sensorial Features by Principal Component Analysis for ANN Machine Learning in Tool Condition Monitoring of CFRP Drilling
3. Huang Y. and Deng Y. 2022. A Hybrid Model Utilizing Principal Component Analysis and Artificial Neural Networks for Driving Drowsiness Detection. Applied Sciences (Switzerland). 12 12 (2022). DOI: https://doi.org/10.3390/app12126007. 10.3390/app12126007
4. Huang Y. and Deng Y. 2022. A Hybrid Model Utilizing Principal Component Analysis and Artificial Neural Networks for Driving Drowsiness Detection. Applied Sciences (Switzerland). 12 12 (2022). DOI: https://doi.org/10.3390/app12126007.
5. A new hybrid approach for feature extraction and selection of electroencephalogram signals in case of person recognition
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