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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM31704
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
· In the modern world, hand gesture recognition systems play a critical role in enhancing human-computer interaction, particularly for applications requiring touch-free controls and intuitive interfacing. This paper presents a comprehensive evaluation system for hand gesture recognition, designed to bridge the gap between gesture detection accuracy and user experience in real-world scenarios. Utilizing advanced machine learning algorithms, real-time data processing, and a feedback-based refinement mechanism, this system aims to improve the accuracy, responsiveness, and usability of gesture recognition technologies. By centralizing essential resources such as dataset libraries, training models, and user feedback modules, this platform addresses key challenges in gesture recognition, such as environmental adaptability, varying gesture clarity, and system robustness. Ultimately, this work seeks to contribute a holistic evaluation framewor k that empowers developers to refine hand gesture recognition systems, making them more accessible and reliable across various domains.
KEYWORDS
Publication Date
12/31/45610
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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