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20172021
most citedImage Matching Using SIFT, SURF, BRIEF and ORB: Performance Comparison for Distorted Images

305 citations · 312 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CV20211 cited

Deep Machine Learning Based Egyptian Vehicle License Plate Recognition Systems

Mohamed Shehata, Mohamed Taha Abou-Kreisha, Hany Elnashar

Automated Vehicle License Plate (VLP) detection and recognition have ended up being a significant research issue as of late. VLP localization and recognition are some of the most e…

cs.CV2019

DomainSiam: Domain-Aware Siamese Network for Visual Object Tracking

Mohamed H. Abdelpakey, Mohamed S. Shehata

Visual object tracking is a fundamental task in the field of computer vision. Recently, Siamese trackers have achieved state-of-the-art performance on recent benchmarks. However, S…

cs.CV20195 cited

Vehicles Detection Based on Background Modeling

Mohamed Shehata, Reda Abo-Al-Ez, Farid Zaghlool +1

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…

cs.CV2018

DensSiam: End-to-End Densely-Siamese Network with Self-Attention Model for Object Tracking

Mohamed H. Abdelpakey, Mohamed S. Shehata, Mostafa M. Mohamed

Convolutional Siamese neural networks have been recently used to track objects using deep features. Siamese architecture can achieve real time speed, however it is still difficult…

cs.CV2018

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

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…

cs.CV2017305 cited

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

Ebrahim Karami, Siva Prasad, Mohamed Shehata

Fast and robust image matching is a very important task with various applications in computer vision and robotics. In this paper, we compare the performance of three different imag…