Open Access

ARTICLE

Enhancing Human Action Recognition with Adaptive Hybrid Deep Attentive Networks and Archerfish Optimization

Ahmad Yahiya Ahmad Bani Ahmad¹, Jafar Alzubi², Sophers James³, Vincent Omollo Nyangaresi^4,5,*, Chanthirasekaran Kutralakani⁶, Anguraju Krishnan⁷

1 Department of Accounting and Finance, Faculty of Business, Middle East University, Amman, 11831, Jordan
2 Faculty of Engineering, Al-Balqa Applied University, Salt, 19117, Jordan
3 Department of Mathematics, Kongunadu College of Engineering and Technology (Autonomous), Tholurpatti, Trichy, 621215, India
4 Department of Computer Science and Software Engineering, Jaramogi Oginga Odinga University of Science and Technology, Bondo, 210-40601, Kenya
5 Department of Electronics and Communication Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Chennai, 602105, India
6 Department of Electronics and Communication Engineering, Saveetha Engineering College (Autonomous), Chennai, 602105, India
7 Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology (Autonomous), Tholurpatti, Trichy, 621215, India

* Corresponding Author: Vincent Omollo Nyangaresi. Email: