*Result*: Developing an intelligent computer vision-based face recognition mechanism.

*Face recognition technology has become crucial in a range of security and authentication applications, however achieving high accuracy and robustness remains challenging. This study presents a unique face recognition approach to develop the accuracy and effectiveness of facial feature assessment that utilized the bidirectional long short-term memory with an enhanced honey bee optimization (BLSTM-EHBO) method. The main objective is to combine the progression learning exceptionality of BLSTM networks with the optimization ability of enhanced honey bee algorithms to build a superior computer vision system that outperforms the conventional methods. To assess the system's performance various parameters are utilized. The proposed method has the ability to contract with real-world issues in face recognition technology, as evidenced by preliminary results that demonstrate significant gains in recognition accuracy (87%), precision (88%), recall (50%), and an F1-Score (60%) when contrasted, to conventional approaches. [ABSTRACT FROM AUTHOR]

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