| Autor: |
S. N. Kakarwal, Ratnadeep R. Deshmukh, Ravindra B. Patil, K. P. Chaudhari |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
2020 International Conference on Smart Innovations in Design, Environment, Management, Planning and Computing (ICSIDEMPC). |
| DOI: |
10.1109/icsidempc49020.2020.9299648 |
| Popis: |
Face recognition is the process of identifying the human face with the help of computerized system mostly for the purpose of security reasons. As the face is very important characteristic of human body through which one can uniquely identify the person. So focusing the face for authentication or identification is at most important for variety of its applications. It is the problem of pattern recognition which can be easily and efficiently solved with artificial neural networks (ANN). Pattern recognition is the process through which particular patterns can be identified, recognized based on the relatedness and similarities between the patterns. Face recognition is having number of applications such as authentication at various offices, organizations or other sectors where security is of utmost important. The proposed methodology for face recognition made use of visible, thermal and fused image database. Thermal imaging detects the heat of the object or face. The artificial neural network is a very efficient technology to enhance the results. Here backpropagation and Levenberg-Marquardt algorithm were compared by using the same database. The Backpropagation algorithm achieved the accuracy of 92.86% and for Levenberg-Marquardt accuracy is 83.92%. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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