Preferred Language
Articles
/
QBcMXJIBVTCNdQwCCK3j
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
...Show More Authors

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).

Scopus Crossref
View Publication
Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Teaching Strategy Based on the Cognitive Model of Daniel in the Development of Achievement and the Motivation of learning the School Mathematics among the Third Intermediate Grade Students
...Show More Authors

This research aims to examine the effectiveness of a teaching strategy based on the cognitive model of Daniel in the development of achievement and the motivation of learning the school mathematics among the third intermediate grade students in the light of their study of "Systems of Linear Equations”. The research was conducted in the first semester (1439/1440AH), at Saeed Ibn Almosaieb Intermediate School, in Arar, Saudi Arabia. A quasi-experimental design has been used. In addition, a (pre & post) achievement test (20 Questions) and a (pre & post) scale of learning motivation to the school mathematics (25 Items) have been applied on two groups: a control group (31Students), and an experimental group (29 Students). The resear

... Show More
View Publication Preview PDF
Publication Date
Tue Dec 25 2018
Journal Name
Summaries Of Working Papers, Research And Experiments
E-learning at the College of Mass Communication, subject: public relations campaigns as a model
...Show More Authors

Publication Date
Sat Mar 29 2014
Journal Name
International Journal Of Academic Research In Progressive Education And Development
The Effects of Problem-Based Learning on Self-Directed Learning Skills among Physics Undergraduates
...Show More Authors

The aim of this study is to compare the effects of three methods: problem-based learning (PBL), PBL with lecture method, and conventional teaching on self-directed learning skills among physics undergraduates. The actual sample size comprises of 122 students, who were selected randomly from the Physics Department, College of Education in Iraq. In this study, the pre- and post-test were done and the instruments were administered to the students for data collection. The data was analyzed and statistical results rejected null hypothesis of this study. This study revealed that there are no signifigant differences between PBL and PBL with lecture method, thus the PBL without or with lecture method enhances the self-directed learning skills bette

... Show More
Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering & Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
...Show More Authors

View Publication
Scopus (10)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
...Show More Authors

View Publication
Crossref (49)
Crossref
Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Keratoconus Severity Detection From Elevation, Topography and Pachymetry Raw Data Using a Machine Learning Approach
...Show More Authors

View Publication
Scopus (15)
Crossref (15)
Scopus Clarivate Crossref
Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
A New Separable Moments Based on Tchebichef-Krawtchouk Polynomials
...Show More Authors

View Publication
Scopus (21)
Crossref (20)
Scopus Clarivate Crossref
Publication Date
Sun Jun 08 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
...Show More Authors

The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

... Show More
View Publication Preview PDF
Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
...Show More Authors

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

... Show More
View Publication Preview PDF
Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Reinforcement Learning-Based Television White Space Database
...Show More Authors

Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

... Show More
View Publication Preview PDF
Scopus (2)
Scopus Clarivate Crossref