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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
The results analyzed in this method show its efficiency.
📌 3 Key Takeaways
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Objective & Hypothesis:Face recognition is one of the topics from which it is difficult to prepare a complete computational model.
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Key Findings & Data:Unlike other detection's these are a high-level task, and a variety of methods have been proposed.
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Conclusion & Impact:The results analyzed in this method show its efficiency.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Face recognition · LBP · Detection
Abstract
Face recognition is one of the topics from which it is difficult to prepare a complete computational model. Unlike other detection's these are a high-level task, and a variety of methods have been proposed. On the other hand, face recognition is needed as a suitable data source for various applications that lead to the recognition of individuals. In this article, we will examine this issue and consider a method based on Local Binary Patterns and provide algorithms for it. The results analyzed in this method show its efficiency.
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Cite This Article
Orhan, Ö., Milani, M., Milani, B. (2020). Face Recognition using Local Binary Patterns. Electronic Letters on Science and Engineering, Volume: 16 Issue: 2. https://ajindex.com/articles/1181008