CGA: a new feature selection model for visual human action recognition-Reference-Cited by-同舟云学术

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CGA: a new feature selection model for visual human action recognition

Published:2020-09-08 Issue:10 Volume:33 Page:5267-5286
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Guha Ritam,Khan Ali Hussain,Singh Pawan Kumar^ORCID,Sarkar Ram,Bhattacharjee Debotosh

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-020-05297-5.pdf

Reference92 articles.

1. Aslan MF, Durdu A, Sabanci K (2020) Human action recognition with bag of visual words using different machine learning methods and hyperparameter optimization. Neural Comput Appl 32:8585–8597

2. Sahoo SP, Ari S (2019) On an algorithm for human action recognition. Expert Syst Appl 115:524–534

3. Saggese A, Strisciuglio N, Vento M, Petkov N (2019) Learning skeleton representations for human action recognition. Pattern Recognit Lett 118:23–31

4. Zhang P, Lan C, Xing J et al (2019) View adaptive neural networks for high performance skeleton-based human action recognition. IEEE Trans Pattern Anal Mach Intell 41:1963–1978

5. Ahmed S, Ghosh KK, Singh PK et al (2020) Hybrid of harmony search algorithm and ring theory-based evolutionary algorithm for feature selection. IEEE Access 8:102629–102645

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2. A Comparative Analysis of XGBoost and LightGBM Approaches for Human Activity Recognition: Speed and Accuracy Evaluation;International Journal of Computational and Experimental Science and Engineering;2024-06-27

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