Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers. The experiment’s result indicates that the J48 classifier with LDA achieves the highest performance with 96.0001% accuracy.
Machine Learning Approach for Facial Image Detection System
Publication Date
Mon Nov 29 2021
Journal Name
Iraqi Journal Of Science
Determining and Estimating the Creep of Tigris Riverbanks at the Baghdad University Camp Using GIS Analytical Symmetrical Difference Method
The Tigris River in Iraq is of highly meandering in several of its parts. So, the largest meandering inside Baghdad City, is in Al-Jadriyah. During its course, the Tigris Riverbanks are facing erosion frequently due to alteration in the geomorphological and hydrological characteristics affecting the river channel. The entire length of Tigris River from the northern entrance of Baghdad to the convergence with Diyala River at southern of Baghdad is about 49 km length. The Tigris River is suffering from the erosion, deposition, and migration conditions. The river migration was found as maximum in the left bank at the side of the University, and lesser in the right bank in the opposite side, Dora. The aim of this study is to measure the magn
... Show More
(1)
