ENHANCING FACIAL EXPRESSION AND ATTRIBUTES RECOGNITION: AN EXPLORATION OF MULTI-TASK LEARNING WITHIN LIGHTWEIGHT NEURAL NETWORKS
Journal Title: International scientific journal Science and Innovation - Year 2023, Vol 2, Issue 11
Abstract
Facial recognition, especially in the domains of expression and attribute detection, has become pivotal in numerous applications. This study delves into the synergistic integration of multi-task learning techniques with lightweight neural networks to address the dual challenges of computational efficiency and robust performance. The research findings underscore the potential of this combined approach, revealing a significant improvement in the recognition of facial expressions and attributes. Furthermore, the proposed framework exhibits enhanced efficiency, making it ideal for real-world applications that demand rapid and accurate facial analysis.
Authors and Affiliations
Agzamova Mohinabonu
Keywords
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- EP ID EP725063
- DOI 10.5281/zenodo.10207749
- Views 61
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