Search Results for author: Mohamed Shehata

Found 6 papers, 1 papers with code

Deep Machine Learning Based Egyptian Vehicle License Plate Recognition Systems

no code implementations24 Jul 2021 Mohamed Shehata, Mohamed Taha Abou-Kreisha, Hany Elnashar

The performance of the developed systems has been tested on real images, and the experimental results demonstrate that the best detection accuracy rate for VLP is provided by using the deep learning method.

BIG-bench Machine Learning License Plate Recognition +3

Vehicles Detection Based on Background Modeling

no code implementations13 Jan 2019 Mohamed Shehata, Reda Abo-Al-Ez, Farid Zaghlool, Mohamed Taha Abou-Kreisha

Background image subtraction algorithm is a common approach which detects moving objects in a video sequence by finding the significant difference between the video frames and the static background model.

Estimation and Tracking of AP-diameter of the Inferior Vena Cava in Ultrasound Images Using a Novel Active Circle Algorithm

no code implementations5 May 2018 Ebrahim Karami, Mohamed Shehata, Andrew Smith

Medical research suggests that the anterior-posterior (AP)-diameter of the inferior vena cava (IVC) and its associated temporal variation as imaged by bedside ultrasound is useful in guiding fluid resuscitation of the critically-ill patient.

Adaptive Polar Active Contour for Segmentation and Tracking in Ultrasound Videos

no code implementations19 Mar 2018 Ebrahim Karami, Mohamed Shehata, Andrew Smith

Detection of relative changes in circulating blood volume is important to guide resuscitation and manage a variety of medical conditions including sepsis, trauma, dialysis and congestive heart failure.

Segmentation

Image Identification Using SIFT Algorithm: Performance Analysis against Different Image Deformations

no code implementations7 Oct 2017 Ebrahim Karami, Mohamed Shehata, Andrew Smith

Image identification is one of the most challenging tasks in different areas of computer vision.

Image Matching Using SIFT, SURF, BRIEF and ORB: Performance Comparison for Distorted Images

1 code implementation7 Oct 2017 Ebrahim Karami, Siva Prasad, Mohamed Shehata

Fast and robust image matching is a very important task with various applications in computer vision and robotics.

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