Human Iris Recognition using Elman Neural Networks
نویسندگان
چکیده
منابع مشابه
Monthly Flow Estimation Using Elman Neural Networks
This paper investigates the application of partially recurrent artificial neural networks (ANN) in the flow estimation for São Francisco River that feeds the hydroelectric power plant of Sobradinho. An Elman neural network was used suitably arranged to receive samples of the flow time series data available for São Francisco River shifted by one month. For that, the neural network input had a de...
متن کاملrodbar dam slope stability analysis using neural networks
در این تحقیق شبکه عصبی مصنوعی برای پیش بینی مقادیر ضریب اطمینان و فاکتور ایمنی بحرانی سدهای خاکی ناهمگن ضمن در نظر گرفتن تاثیر نیروی اینرسی زلزله ارائه شده است. ورودی های مدل شامل ارتفاع سد و زاویه شیب بالا دست، ضریب زلزله، ارتفاع آب، پارامترهای مقاومتی هسته و پوسته و خروجی های آن شامل ضریب اطمینان می شود. مهمترین پارامتر مورد نظر در تحلیل پایداری شیب، بدست آوردن فاکتور ایمنی است. در این تحقیق ...
Iris Recognition Using Wavelet Transform and Artificial Neural Networks
In this approach to get more accuracy of the iris recognition, is composed of many steps: capturing the iris image, determining the location of the iris boundaries, normalization, preprocessed using median filter to remove noise, using wavelet transform for two types of filter, Haar and Daubechies (db4), in order to extract the features and finally using the matching by artificial feed forward ...
متن کاملIRIS Pattern Recognition using Self-Organizing Neural Networks
With an increasing emphasis on security, automated personal identification based on biometrics has been receiving extensive attention over the past decade. Iris recognition, as an emerging biometric recognition approach is receiving interest in both research and practical applications. Iris is a kind of physiological biometric feature. It contains unique texture and is complex enough to be used...
متن کاملIris Recognition Using Discrete Cosine Transform and Artificial Neural Networks
Problem statement: The study presented an efficient Iris recognition system. Approach: The design used the discrete cosine transform for feature extraction and artificial neural networks for classification. The iris images used in this system were obtained from the CASIA database. Results: A robust system for iris recognition was developed. Conclusion: An iris recognition system that produces v...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: JOURNAL OF EDUCATION AND SCIENCE
سال: 2010
ISSN: 2664-2530
DOI: 10.33899/edusj.2010.57988