التفاصيل البيبلوغرافية
| العنوان: |
Dynamic gender recognition using Yolov7 with minimal frame per second. |
| المؤلفون: |
Mariyappan, Shanmuga Sundari, Ammangatambu, Mayukha Mandya, Sai, Bodicherla Chandana |
| المصدر: |
AIP Conference Proceedings; 2024, Vol. 3028 Issue 1, p1-6, 6p |
| مصطلحات موضوعية: |
DEEP learning, FRAMES (Social sciences) |
| مستخلص: |
Deep learning-based gender detection is demonstrating its effectiveness in a variety of areas, including healthcare, marketing, security, and many others. Deep learning models have boosted their capability to identify objects in images and videos. This paper includes an extensive description of gender detection using the framework YOLOv7, including architecture, limitations, and performance. The research study analyzes YOLOv7's performance in detecting gender from facial images and videos, with a particular focus on lightning-fastness, precision, and robustness. The experimental results prove that YOLOv7 outscored YOLOv7x. The paper addresses the YOLOv7 framework's potential in various areas such as healthcare, marketing, and security. Overall, this paper demonstrates the potency of YOLOv7 in detecting gender. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
Complementary Index |
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