Hadeer Adel

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Sheilagh Ogilvie

University of Oxford

Andreas Umland

National University of "Kyiv-Mohyla Academy"

Armando Marques-Guedes

UNL - New University of Lisbon

Eva Botella-Ordinas

Universidad Autónoma de Madrid

Shadi Davari

Tehran University of Medical Sciences

Christian Burgers

Vrije Universiteit Amsterdam

Maciej Witek

University of Szczecin, Poland

Fidel J Tavárez

Queens College of the City University of New York

Karen Ng

Vanderbilt University

Kepa Korta

University of the Basque Country, Euskal Herriko Unibertsitatea

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Papers by Hadeer Adel

Novel Single Image deblurring Technique using Sparse representation and Discrete Radon Transform

2015 25th International Conference on Computer Theory and Applications (ICCTA), 2015

In this paper, a novel single image deblurring technique based on sparse representation and radon... more In this paper, a novel single image deblurring technique based on sparse representation and radon transform is presented. The Sparse representation is used to make an initial estimation of the latent sharp image. Then, a set of directional filters are applied to the blurry and noisy image to reduce the noise while maintaining the blurry information on the orthogonal direction. After that an initial kernel estimation at different angles is performed using the initial latent image that was produced using sparse representation. Each estimated kernel is transformed to radon transform and the set of projections at different angles are stored. An inverse radon transform is applied to make a final kernel estimation. Finally, the Wiener deconvolution is performed to estimate the final latent sharp image. Experimental results showed the effectiveness of the proposed technique. The best obtained PSNR is 28.233 at 0.04 noise ratio, whereas the best obtained SSIM is 0.896769 at also 0.04 noise ...

Development of Large Area Motion Tracking System

2019 7th International Japan-Africa Conference on Electronics, Communications, and Computations, (JAC-ECC), 2019

Different systems focus on the analysis of the motion of the human body, meanwhile these systems ... more Different systems focus on the analysis of the motion of the human body, meanwhile these systems face a lot of challenges such as the small range and the high cost. This paper represents a proposed system for detecting the motion of a moving body called Large Area Motion Tracking (LAMT). This system enables the researchers to study and follow up the human body motion in large areas. This can be achieved by developing a video display of a laser beam motion using a photo detector and an optical system. The main advantages of the proposed system are the speed, the low price, the accurate run and the real-time detection capability., also it will be suitable for the indoor and the outdoor applications.

A Comparative Study On Image Deblurring Techniques

Image blur is a common problem that occurs when recording digital images due to camera shake, lon... more Image blur is a common problem that occurs when recording digital images due to camera shake, long exposure time, or movement of objects. As a result, the recorded image is degraded and the recorded scene becomes unreadable. Recently, the field of blur removal has gained increasing interest in a lot of researches. The problem is known as blind deconvolution if the only available information is the blurred image and there is no knowledge about the blurring model or the Point Spread Function (PSF). In this case, the basic target of the process is to recover both the blur kernel and the deblurred (latent) image, simultaneously. In this paper, we introduced a comprehensive study on the image deblurring, type of blur, noise model and finally a comparative study of different image deblurring techniques. We performed several experiments to evaluate these techniques in terms of performance, blur type, Peak Signal to Noise Ratio and structural similarity (SSIM).

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The Impact of Financial Reporting Quality on Firm’s Financial Performance: Evidence from Egypt

International Journal of Academic Research in Accounting, Finance and Management Sciences

Medical Community Perspectives Regarding the Egyptian Medical Licensing Exam: A Mixed-Method Study

Cureus

Background: Although national licensing examinations (NLEs) may be a costly process, they can pre... more Background: Although national licensing examinations (NLEs) may be a costly process, they can predict performance of medical practitioners for many years following graduation. The current licensing requirements do not fulfill this function as there are no clear performance criteria for them. Therefore, new requirements should be developed and announced. Objective: The study aims to develop a framework for the Egyptian Medical Licensing Exam (EMLE) by exploring the opinions and perceptions of Egyptian health practitioners and medical educators. Methods: This study is a two-phase exploratory mixed-method study. An online discussion forum was conducted with medical practitioners and educators concerning the development of the EMLE. Then, an online survey was distributed to explore the opinions of medical practitioners and educators about the EMLE. Results: Fifty medical practitioners and educators participated in the discussion forum about the development of the EMLE, while 266 participants responded to the online survey. The responses of the participants contributed to the development of a framework for the EMLE that is divided into two main sections, the exam logistics and the exam set up. The exam logistics included the exam committee, prerequisites for the exam, the admission criteria and fees, and validity of the license. The exam set up included exam setting, structure, pass marks, and exam retake policy. Conclusion: The study concluded that medical practitioners and educators could contribute greatly to the planning for the EMLE. Their opinions are based on their experiences and include the timing of the exam, blueprinting, assessment methods, psychometrics and retake.

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Improving Crisis Events Detection Using DistilBERT with Hunger Games Search Algorithm

Mathematics

This paper presents an alternative event detection model based on the integration between the Dis... more This paper presents an alternative event detection model based on the integration between the DistilBERT and a new meta-heuristic technique named the Hunger Games Search (HGS). The DistilBERT aims to extract features from the text dataset, while a binary version of HGS is developed as a feature selection (FS) approach, which aims to remove the irrelevant features from those extracted. To assess the developed model, a set of experiments are conducted using a set of real-world datasets. In addition, we compared the binary HGS with a set of well-known FS algorithms, as well as the state-of-the-art event detection models. The comparison results show that the proposed model is superior to other methods in terms of performance measures.

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Novel Single Image deblurring Technique using Sparse representation and Discrete Radon Transform

2015 25th International Conference on Computer Theory and Applications (ICCTA), 2015