Yahya Ahmed Yahya Dallal Bashi
Research InterestsArtificial Intelligence
| Gender | MALE |
|---|---|
| Place of Work | Presidency |
| Position | Division Manager |
| Qualification | Master |
| Speciality | Artificial Intelligence |
| yahya.ahmed87@ntu.edu.iq | |
| Phone | 07740870848 |
| Address | Malta Mamostayan, Duhok, Dohuk, Iraq |
Yahya Ahmed Dallal Bashi holds a Master's degree in Computer Engineering from Jordan University of Science and Technology, which he completed in 2013. He is currently working at the Presidency of Northern Technical University, contributing to the advancement of technical and vocational education in Iraq. He has extensive research experience in the fields of Artificial Intelligence and image processing, with a particular focus on medical image processing for disease detection and diagnosis. His numerous published studies aim to deliver innovative solutions that enhance practical and educational applications.
Skills
Artificial Intelligence (75%)
Machine Learning (80%)
Deep Learning and Neural Networks (77%)
Image Segmentation (80%)
Computer Networking (80%)
Matlab (85%)
MS Office (90%)
Academic Qualification
Master Degree
Feb 10, 2010 - Feb 10, 2013Working Experience
in Duhok Polytechnic University, Zakho, Iraq [Assistant Lecturer]
Nov 1, 2013 - Apr 1, 2016in Duhok Polytechnic University, Zakho, Iraq
in Al-Hadba University, Mosul,Iraq [Assistant Lecturer]
Apr 1, 2016 - Feb 3, 2023in Al-Hadba University, Mosul,Iraq
In Jordan University of Science and Technology, Irbid, Jordan [Teacher Assistant]
Feb 1, 2010 - Feb 1, 2012In Jordan University of Science and Technology, Irbid, Jordan
in Northern Technical University, Mosul, Iraq [Assistant Lecturer]
May 7, 2023 - Presentin Northern Technical University, Mosul, Iraq
Publications
Multi-thresholding image segmentation using genetic algorithm
Jan 1, 2011publisher The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp)
mage segmentation is one of the essential problems in computer vision and image processing. It works by partitioning a digital image into multiple regions or sets. The increasing importance of image segmentation in multiple issues and applications has motivated the researchers to propose and improve algorithms that support image segmentation process. There are many methods for image segmentation. In this paper, we use thresholding technique with genetic algorithm to find optimal thresholds between the various objects and the background.