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Retaj Yousri

Former Research Assistant

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Retaj Yousri received her B.Sc. degree in biomedical engineering from Helwan University, Cairo, Egypt, in 2020. She is currently pursuing an M.Sc. degree in micro-electronics system design with the School of Engineering and Applied Sciences, Nile University, Giza, Egypt. She is currently working as a Research Assistant at Wireless Intelligent Networks Center (WINC), Nile University. Her research interests include signal processing, image processing, computer vision, optimization, and neuroscience.

  • Best paper award titled "Patient-Specific Epileptic Seizures Prediction based on Support Vector Machine" at the 32nd International Conference on Microelectronics (ICM).
Recent Publications

A Deep Learning-Based Benchmarking Framework for Lane Segmentation in the Complex and Dynamic Road Scenes

Automatic lane detection is a classical task in autonomous vehicles that traditional computer vision techniques can perform. However, such techniques lack reliability for achieving high accuracy while maintaining adequate time complexity in the context of real-time detection in complex and dynamic road scenes. Deep neural networks have proved their ability to achieve competing accuracy and time
Artificial Intelligence

A Novel Power-Aware Task Scheduling for Energy Harvesting-Based Wearable Biomedical Devices Using FPA

Power management and saving in energy harvesting-based biomedical wearable devices are mandatory to ensure prolonged and stable operation under a stringent power budget. Thus, power-aware task scheduling can play a key role in minimizing energy consumption to improve system durability while maintaining device functionality. This paper proposes a novel biosensor task scheduling for optimizing

Circuit Theory and Applications

A Preprocessing Approach to Improve the Performance of Inception v3-based Face Shape Classification

Face shape classification is considered one of the trending topics in the artificial intelligence research field. Face shape classification can be employed in many broad-scoped projects, such as hairstyle recommendation systems in the beauty and fashion industry. In this paper, the inception v3 model was employed to reach the highest possible performance for classifying the different face shapes

Software and Communications
Research Tracks
  • Signal Processing
  • Image Processing
  • Computer Vision
  • Optimization and Neuroscience