Preferred Language
Articles
/
ijs-247
Intelligent Age Estimation From Facial Images Using Machine Learning Techniques
...Show More Authors

     Lately, a growing interest has been emerging in age estimation from face images because of the wide range of potential implementations in law enforcement, security control, and human computer interactions. Nevertheless, in spite of the advances in age estimation, it is still a challenging issue. This is due to the fact that face aging process is not only set by distinct elements, such as genetic factors, but by extrinsic factors, such as lifestyle, expressions, and environment as well. This paper applied machine learning technique to intelligent age estimation from facial images using J48 classifier on FG_NET dataset. The proposed work consists of three phases; the first phase is image preprocessing which include five stages: gray scale image, noise removable, face detection, image size normalization and clipping process. The second phase is a data mining process which includes three stages: feature extraction, feature selection and classification using j48 classifier. The third phase includes two stages, estimation and evaluation. FG-NET dataset is used which is divided into three classes; first class represents (3-7), (26-30) ages and this class represents the ages from 3 to 7 years and from 26 to 30 years because this class have four attributes from any one of this images, second class represents (8-25) ages and this class represents the ages from 8 to 25 years because this class have five attributes from any one of this images, last class represents (31-50) ages and have nine attributes from any one of this images. The Experimental results illustrate that the proposed system can give results with high precision and low time complexity. The practical evaluation of the proposed system gives accuracy up to 89.13 % with time taken of 0.023.

View Publication Preview PDF
Quick Preview PDF
Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Image Compression Using Deep Learning: Methods and Techniques
...Show More Authors

     In recent years images have been used widely by online social networks providers or numerous organizations such as governments, police departments, colleges, universities, and private companies. It held in vast databases. Thus, efficient storage of such images is advantageous and its compression is an appealing application. Image compression generally represents the significant image information compactly with a smaller size of bytes while insignificant image information (redundancy) already been removed for this reason image compression has an important role in data transfer and storage especially due to the data explosion that is increasing significantly. It is a challenging task since there are highly complex unknown correlat

... Show More
View Publication Preview PDF
Scopus (12)
Crossref (5)
Scopus Crossref
Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Classification Based on Weighted Extreme Learning Machine
...Show More Authors

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning
...Show More Authors

     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

... Show More
View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Quantifying Suicidal Ideation on Social Media using Machine Learning: A Critical Review
...Show More Authors

Suicidal ideation is one of the severe mental health issues and a serious social problem faced by our society. This problem has been usually dealt with through the psychological point of view, using clinical face to face settings. There are various risk factors associated with suicides, including social isolation, anxiety, depression, etc., that decrease the threshold for suicide. The COVID-19 pandemic further increases social isolation, posing a great threat to the human population. Posting suicidal thoughts on social media is gaining much attention due to the social stigma associated with the mental health. Online Social Networks (OSN) are increasingly used to express the suicidal thoughts. Recently, a top Indian actor industry took th

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (3)
Scopus Crossref
Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
...Show More Authors

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select

... Show More
View Publication Preview PDF
Scopus (17)
Crossref (14)
Scopus Clarivate Crossref
Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
...Show More Authors

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
Facial Expression Recognition Based on Deep Learning: An Overview
...Show More Authors

      Recognizing facial expressions and emotions is a basic skill that is learned at an early age and it is important for human social interaction. Facial expressions are one of the most powerful natural and immediate means that humans use to express their feelings and intentions. Therefore, automatic emotion recognition based on facial expressions become an interesting area in research, which had been introduced and applied in many areas such as security, safety health, and human machine interface (HMI). Facial expression recognition transition from controlled environmental conditions and their improvement and succession of recent deep learning approaches from different areas made facial expression representation mostly based on u

... Show More
View Publication Preview PDF
Scopus (3)
Scopus Crossref
Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Sentiment analysis in arabic language using machine learning: Iraqi dialect case study
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
A Survey on Arabic Text Classification Using Deep and Machine Learning Algorithms
...Show More Authors

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

... Show More
Scopus (8)
Crossref (4)
Scopus Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
...Show More Authors

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

... Show More
View Publication
Scopus Crossref