Ph.D.

Oct 27, 2025 - Present

Ph.D. in computer engineering

New Novel FPGA Based Image Encryption Methods Using Multiple Chaotic Maps

Dec 17, 2024

publisher IEEE

DOI http://doi.org/10.12928/telkomnika.v19i2.18322

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Real time ear recognition using deep learning

Apr 1, 2021

Journal TELKOMNIKA Telecommunication, Computing, Electronics and Control

DOI http://doi.org/10.12928/telkomnika.v19i2.18322

Issue 2

Volume 19

Automatic identity recognition of ear images represents an active area of interest within the biometric community. The human ear is a perfect source of data for passive person identification. Ear images can be captured from a distance and in a covert manner; this makes ear recognition technology an attractive choice for security applications and surveillance in addition to related application domains. Differing from other biometric modalities, the human ear is neither affected by expressions like faces are nor do need closer touching like fingerprints do. In this paper, a deep learning object detector called faster region based convolutional neural networks (Faster R-CNN) is used for ear detection. A convolutional neural network (CNN) is used as feature extraction. principal component analysis (PCA) and genetic algorithm are used for feature reduction and selection respectively and a fully connected artificial neural network as a matcher. The testing proved the accuracy of 97.8% percentage of success with acceptable speed and it confirmed the accuracy and robustness of the proposed system.

New Novel FPGA Based Image Encryption Methods Using Multiple Chaotic Maps

Dec 17, 2024 - Dec 19, 2024

Publisher IEEE

Country egypt

Location Cairo, Egypt