Indian Journal of Science and Technology
Year: 2023, Volume: 16, Issue: 17, Pages: 1295-1301
Shoba Rani Salvadi1*, D Nagendra Rao2, S Vathsal3
1Research scholar, Jawaharlal Nehru Technological University, Hyderabad, Telangana, India
2Professor and Principal, Abhinav-Hitech College of Engineering, Moinabad, Telangana, India
3Retired DRDO Scientist
Email: [email protected]
Received Date:17 February 2023, Accepted Date:12 March 2023, Published Date:02 May 2023
Objective: To Develop an intelligent and innovative method to categorize the Gender by focusing facial images. Method: We integrate the characteristics of Bidirectional Associative Memory (BAM) and Deep Octonion Networks (DON) to enhance the Gender detection in real time applications. The developed hybrid model is called Visual Mapping of BAM and DON (VMBAD). To validate the projected system, we make use of 4000 images and 126 different subjects as a data set to train the proposed approach and simultaneously compare our results with the existing methods using the same data set. Findings: The projected technique improves the performance of the system by 3 -5 % in terms of sensitivity, accuracy, and precision when compared with the existing approaches (vide figures 4-7). Novelty: The designed method enhances both the accuracy and precision of image by nearly 4% and 2% respectively when compared with the reported work.
Keywords: Artificial Intelligence; Bidirectional Associative Memories; Gender Identification; Deep Octonion Networks; Deep Quaternion Networks
© 2023 Salvadi et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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