Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal International Journal of Engineering, Technology and Natural Sciences (IJETS) Indonesian Journal of Electrical Engineering and Computer Science
Yahya Ismail Ibrahim
Unknown Affiliation
Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Modified three-term conjugate gradient algorithm and its applications in image restoration Yahya Ismail Ibrahim; Hisham Mohammed Khudhur
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1510-1517

Abstract

In image restoration, the goal is often to bring back a high-quality version of an image from a lower-quality copy of it. In this article, we will investigate one kind of recovery issue, namely recovering photos that have been blurred by noise in digital photographs (sometimes known as "salt and pepper" noise). When subjected to noise at varying frequencies and intensities (30,50,70,90). In this paper, we used the conjugate gradient algorithm to Restorative images and remove noise from them, we developed the conjugate gradient algorithm with three limits using the conjugate condition of Dai and Liao, where the new algorithm achieved the conditions for descent and global convergence under some assumptions. According to the results of the numerical analysis, the recently created approach is unequivocally superior to both the fletcher and reeves (FR) method and the fletcher and reeves three-term (TTFR) metod. Use the structural similarity index measure (SSIM), which is used to measure image quality and the higher its value, the better the result. The original image was compared with all the noisy images and each according to the percentage of noise as well as the images processed with the four methods.
Personal Identification Using Palm Features Recognition Hanaa Mahmood; Yahya Ismail Ibrahim; Nagham Tharwat Saeed
Jurnal Internasional Teknik, Teknologi dan Ilmu Pengetahuan Alam Vol 4 No 2 (2022): International Journal of Engineering, Technology and Natural Sciences
Publisher : University of Technology Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (312.68 KB) | DOI: 10.46923/ijets.v4i2.170

Abstract

Personal recognition is meant for finding a way for establishment of connections between the person and his/her biometrical features. Such system is depending various data types such as facial images, voice and limbs. In this paper, palm print recognition is made using deep learning paradigms such as feed forward neural network (FFNN). The palm features are extracted by tracking the principal lines of palm skin. This involves performing of pixel to pixel analysis by comparing pixel value with its four sides neighbors. FFNN model is tuned up using ABC-KNN algorithm then used for classification. The proposed system has yielded good recognition accuracy score of 98.66%.
Co-Authors Hanaa Mahmood Hisham Mohammed Khudhur Nagham Tharwat Saeed