International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

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A Gender Classification And Age Detection Using Face Recognition

Author(s) Aarti Deepak Bakare, Suraj Shivaji Redekar
Country India
Abstract This study presents a novel approach to simultaneous gender and age recognition by including emotional context using a mask region-based convolution neural network (Mask R-CNN). The suggested approach makes exact gender and age categorization possible by using deep learning to examine facial traits and emotions. The model captures the complex relationship between emotional states and face characteristics by
extending Mask R-CNN to include emotional signals. By enhancing overall system performance, this integration offers a more comprehensive comprehension of human behavior. The suggested method achieves state-of-the-art accuracy in gender and age recognition while capturing emotional nuances in facial expressions, as demonstrated by empirical data. This work advances the development of multimodal human-centric systems and has potential applications in a variety of domains, including surveillance, human-computer interaction, and
tailored experience.
Keywords Mask RCNN, convolutional neural networks, deep learning, segmentation, object detection, Computer Vision, Facial Landmark Detection, Instance Segmentation, Transfer Learning
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 5, Issue 6, November-December 2023
Published On 2023-12-11
Cite This A Gender Classification And Age Detection Using Face Recognition - Aarti Deepak Bakare, Suraj Shivaji Redekar - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.10176
DOI https://doi.org/10.36948/ijfmr.2023.v05i06.10176
Short DOI https://doi.org/gs84cj

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