Zakaria Senousy

• C programming
• Java programming
• Microprocessor systems
• High performance computing
• Operating systems
• Database systems

• M.S. in Computer Engineering, Arab Academy for Science and Technology (AAST)
• B.S. in Computer Engineering, Arab Academy for Science and Technology (AAST)

Histopathological Image Segmentation using Convolutional Neural Networks

In computer vision, image segmentation is the process of partitioning a digital image into multiple segments. The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyse. More precisely, image segmentation is the process of assigning a label to every pixel in an image such that pixels with the same label share certain characteristics. The aim of the PhD project is to build and develop an object detection model based on Convolution Neural Network (CNN) to address problems of semantic segmentation in histopathological images. Some of these problems is the difficulty of classifying tiny objects as well as the lack of scene understanding. The research goal is to build flexible models which are efficient and robust for nuclei segmentation.

• Mohamed Gaber
  
• Mohamed Abdelsamea

Sherif F. Fahmy, Zakaria Senousy, Ahmed Fahmy, "Providing QoS in Contention Management for Software Transactional Memory" , 13th International Computer Engineering Conference Cairo University, December 27-28, 2017 "Boundless Smart Societies" (2017) 

Zakaria Senousy, Sherif F. Fahmy, Ahmed Fahmy, “Throughput and Wasted Work in Contention Management for Software Transactional Memory”, ICATAS, UTM, Malaysia, 2018.

• Google Scholar