Presentation

Real-time action localization, Cairo University - Faculty of Computers and Information, :
application/pdf iconreal-time_action_localization.pdf
Semantic web and Its applications, Cairo University - Faculty of Computers and Information, :
application/pdf iconsemantic_web_and_its_applications.pdf
Optimization Problems and algorithms, Banha University - faculty of Computers and Information, :
application/pdf iconoptimization_problems_and__algorithms.pdf

Algorithms are the key engine in numerous methods, techniques and applications. Meanwhile, The Applications’ Data is keep getting bigger and bigger exponentially. Due to these new complexities, using parallelism to enhance the performance of large-scale programs becomes more and more vital. In this paper we propose an OpenMP inspired parallel version of the Whale optimization algorithm; PWhale, it is automatically detect the number of available processors and divide the workload automatically among them to accomplish the best use of available resources.

Handwritten manuscripts image binarization, Banha University - faculty of Computers and Information, :
application/pdf iconhandwritten_manuscripts_image_binarization.pdf

Since the importance of the optimization algorithms in many real-life applications. Optical character recognition, word spotting, and other application need a cleared binarized image. A cleared binarized image without any distortion or hidden character. In this lecture, a quick review about the handwritten manuscripts problems and solutions will be presented. In addition to, the comparison between different binarization methods will be presented. 

A Hybrid Sine Cosine Optimization Algorithm for Solving Global Optimization Problems, Banha University - faculty of Computers and Information, :
application/pdf icona_hybrid_sine_cosine_optimization_algorithm_for_solving_global_optimization_problems.pdf

In this paper, a hybrid sine cosine optimization (denoted as HSCO) algorithm is proposed, in which a local search strategy is hybridized with the sine cosine optimization. The local search strategy aims to enhance the solutions and to prevent premature convergence of the population. By this way, the algorithm can avoid the running without any improvements in the obtained results. The simulations were conducted on a set of the benchmark problems and compared to other optimization techniques that reported in the literature.

CT Liver Segmentation using Artificial Bee Colony Optimization, Banha University - faculty of Computers and Information, :
application/pdf iconct_liver_segmentation_using_artificial_bee_colony_optimization.pdf

The automated segmentation of liver is an essential phase in liver diagnosis in medical images. In this paper, the artificial bee colony optimization algorithm (ABC) is used as a clustering technique to segment the whole liver. ABC calculates the centroids of clusters in CT liver image and extracts a binary image for each cluster. Using some morphological operations can help to remove small and thin regions, which represents parts of flesh around liver, sharp edges of organs and small lesions inside the liver. Then the large regions in each cluster binary image are filled.