Papers by Ruaa Al-Falluji
Weka-An Environment for Knowledge Discovery
IP security by Ruaa Adeeb
Virtual Reality Softwares
Genetic Algorithms Genetic Algorithms Agenda
Chapter 1 Data Mining: A First View
Single Image Super Resolution Algorithms: A Survey and Evaluation
Image processing sub branch that specifically deals with the improvement, of images and videos, r... more Image processing sub branch that specifically deals with the improvement, of images and videos, resolution without compromising the detail and visual effect but rather enhances the two, is known as Super Resolution. Multiple (multiple input images and one output image) or single (one input and one output) low resolution images are converted to high resolution. Single image super resolution algorithms are more practical since multiple images are not always available. The paper presents a survey of recent single image super resolution methods that are based on the use of external database to predict the values of missing pixels in high resolution image. Keywords—Super resolution, Sparese dictionary, Random forest, Convolution neural network
The numerous problems of the traditional security technologies have led to a rise in developing b... more The numerous problems of the traditional security technologies have led to a rise in developing biometric systems. Many traditional biometric systems, such as fingerprint, face, and iris systems have been studied extensively in the previous decades .Nowadays the concept of using the dorsal vein pattern in authentication that uses the vast network blood vessels underneath a person's skin showed to be a proven biometric technique. Different trails have been done to extract veins patterns and build systems that can give good performance. In this paper, we proposed an automatic system for human identification based on their dorsal vein patterns. Within this approach preprocessing steps are implemented to get the enhanced grayscale images with visible and clear veins. Two features extraction techniques are used, Principle Component Analysis (PCA) and Scale Invariant Feature Transform (SIFT), to get eigenveins and keypoints respectively. Statistical distance classifiers are implemente...
Color ,Shape and Texture based Fruit Recognition System
The paper presents an automated system for classification of fruits. A dataset containing five di... more The paper presents an automated system for classification of fruits. A dataset containing five different fruits was constructed using an ordinary camera. All the fruits were analyzed on the basis of their color (RGB space), shape and texture and then classified using different classifiers to find the classifier that gives the best accuracy. Gray Level Cooccurance Matrix(GLCM) is used to calculate texture features .Best accuracy was achieved by support vector machine (svm). All the processing was carried out in Matlab. Keywords—computer vision, pattern recognition, support vector machine, texture features.
Computers, Materials & Continua, 2021
IEEE Access, 2019
In single image super resolution problems, the recent feed forward deep learning architectures us... more In single image super resolution problems, the recent feed forward deep learning architectures use residual connections in order to preserve local features and carry them through the next layer. In a simple residual skip connection, all the features of the earlier layer are concatenated with the features of the current layer. A simple concatenation of features does not exploit the fact that some features may be more useful than other features and vice versa. To overcome this limitation, we propose an extended architecture (baby neural network) which will have input as the features learned from the previous layer and output a multiplication factor. This multiplication factor will give importance to the given feature and thus help in training the current layer's features more accurately. The proposed model clearly outperforms existing works.
International Journal of Computer Applications, 2017
Alzheimer's disease(AD) is a neurological disease. It affects memory of the patient. The liveliho... more Alzheimer's disease(AD) is a neurological disease. It affects memory of the patient. The livelihood of the people that are diagnosed with AD. Magnetic resonance imaging (MRI) is one of the most commonly used imaging modality for the diagnosis of Alzheimer's. Different features and classifiers that are used Computer Aided Diagnosis (CAD) for diagnosis of Alzheimer's are presented.
International Journal of Computer Applications, 2016
A system for detecting Diabetic Macular Edema (DME) using Optical Coherence Tomography (OCT) volu... more A system for detecting Diabetic Macular Edema (DME) using Optical Coherence Tomography (OCT) volumes is presented. In preprocessing stage noise removal and flattening of scans is done which is followed by Local binary pattern feature extraction. The extracted features are then classified using linear support vector machine classifier. The proposed system achieved an specificity and sensitivity of 100% and 86.67% respectively.
Computers, Materials & Continua
The latest studies with radiological imaging techniques indicate that X-ray images provide valuab... more The latest studies with radiological imaging techniques indicate that X-ray images provide valuable details on the Coronavirus disease 2019 (COVID-19). The usage of sophisticated artificial intelligence technology (AI) and the radiological images can help in diagnosing the disease reliably and addressing the problem of the shortage of trained doctors in remote villages. In this research, the automated diagnosis of Coronavirus disease was performed using a dataset of X-ray images of patients with severe bacterial pneumonia, reported COVID-19 disease, and normal cases. The goal of the study is to analyze the achievements for medical image recognition of state-of-the-art neural networking architectures. Transfer Learning technique has been implemented in this work. Transfer learning is an ambitious task, but it results in impressive outcomes for identifying distinct patterns in tiny datasets of medical images. The findings indicate that deep learning with X-ray imagery could retrieve important biomarkers relevant for COVID-19 disease detection. Since all diagnostic measures show failure levels that pose questions, the scientific profession should determine the probability of integration of X-rays with the clinical treatment, utilizing the results. The proposed model achieved 96.73% accuracy outperforming the ResNet50 and traditional Resnet18 models. Based on our findings, the proposed system can help the specialist doctors in making verdicts for COVID-19 detection.
IEEE Access
The internet is growing at a rapid pace offering multiple web-based applications catering to the ... more The internet is growing at a rapid pace offering multiple web-based applications catering to the changing needs and demands of customers. Nevertheless, extensive use of internet services has potentially exposed the threats of data security and reliability. With technological advancements, cyber threats have also become more sophisticated with the blend of distinctive forms of attacks to cause potential damage. The increase in the number and variety of cyber attacks is inevitable; hence it is imperative to improve the efficiency of the cyber security systems. This research aims to compare different neural network models to distinguish malicious acts from non-malicious ones. The examined models are trained, validated, and tested using two datasets(cyber-physical subsystem dataset and KDD dataset). The performance of the studied models is measured using the confusion matrix. For the cyber-physical subsystem dataset, binary classification and multi-class classification are used for evaluating the models. In the KDD dataset, binary classification is the only classification approach because the dataset contains two classes, regular (normal actions) and harmful (malicious actions). In general, the results in binary classification are more encouraging than in multi-class classification. Among all the models, the PNN model achieves the best performance, while the GRNN model is the fastest one. Although PNN's runtime is slightly higher than the GRNN model, we can claim that the PNN is the best model for our data because a trade-off between the performance and run time can be obtained.
The numerous problems of the traditional security technologies have led to a rise in developing b... more The numerous problems of the traditional security technologies have led to a rise in developing biometric systems. Many traditional biometric systems, such as fingerprint, face, and iris systems have been studied extensively in the previous decades .Nowadays the concept of using the dorsal vein pattern in authentication that uses the vast network blood vessels underneath a person's skin showed to be a proven biometric technique. Different trails have been done to extract veins patterns and build systems that can give good performance. In this paper, we proposed an automatic system for human identification based on their dorsal vein patterns. Within this approach preprocessing steps are implemented to get the enhanced grayscale images with visible and clear veins. Two features extraction techniques are used, Principle Component Analysis (PCA) and Scale Invariant Feature Transform (SIFT), to get eigenveins and keypoints respectively. Statistical distance classifiers are implemented for classification. Finally the results from both classifiers are fused using simple min rule. The system has been successfully tested on a database of 100 users using MATLAB version 2009. The obtained results show that the proposed system outperforms the results of each individual system (PCA, SIFT).
Biometric is newest technology in the security field. It uses the inherent characteristic to auth... more Biometric is newest technology in the security field. It uses the inherent characteristic to authenticate persons. This in turn will enhance the reliability of the security systems compared to the traditional based authentication systems such as password or code and solve many of the problems that appeared in the traditional based systems. This leads to using biometrics systems widely in many applications. Many features in the human's body can be used as biometrics if they meet specific requirements .Each one of these biometrics have strength and weakness points. This paper will discuss the commonly used biometrics.
—The paper presents an automated system for classification of fruits. A dataset containing five d... more —The paper presents an automated system for classification of fruits. A dataset containing five different fruits was constructed using an ordinary camera. All the fruits were analyzed on the basis of their color (RGB space), shape and texture and then classified using different classifiers to find the classifier that gives the best accuracy. Gray Level Co-occurance Matrix(GLCM) is used to calculate texture features .Best accuracy was achieved by support vector machine (svm). All the processing was carried out in Matlab.
A system for detecting Diabetic Macular Edema (DME) using Optical Coherence Tomography (OCT) volu... more A system for detecting Diabetic Macular Edema (DME) using Optical Coherence Tomography (OCT) volumes is presented. In preprocessing stage noise removal and flattening of scans is done which is followed by Local binary pattern feature extraction. The extracted features are then classified using linear support vector machine classifier. The proposed system achieved an specificity and sensitivity of 100% and 86.67% respectively.
Alzheimer's disease(AD) is a neurological disease. It affects memory of the patient. The liveliho... more Alzheimer's disease(AD) is a neurological disease. It affects memory of the patient. The livelihood of the people that are diagnosed with AD. Magnetic resonance imaging (MRI) is one of the most commonly used imaging modality for the diagnosis of Alzheimer's. Different features and classifiers that are used Computer Aided Diagnosis (CAD) for diagnosis of Alzheimer's are presented.
The world has become increasingly interconnected in terms of technology. The use of internet has ... more The world has become increasingly interconnected in terms of technology. The use of internet has grown dramatically. Internet plays an important role for the today's business. Every organization wants to secure their moving data because significant data loss can damage the business continuity. So the necessity of network security became obvious. The goal of this paper is to overview the network layer security mechanisms, Internet Protocols Security (IPSec), standard framework and end-to-end architecture .This paper also identifies the services , operation modes of IPSec and discusses the Virtual Private Network (VPN) as an application of IPSec.
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Papers by Ruaa Al-Falluji