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Proposed Face Detection Classification Model Based on Amazon Web Services Cloud (AWS)
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One of the most important features of the Amazon Web Services (AWS) cloud is that the program can be run and accessed from any location. You can access and monitor the result of the program from any location, saving many images and allowing for faster computation. This work proposes a face detection classification model based on AWS cloud aiming to classify the faces into two classes: a non-permission class, and a permission class, by training the real data set collected from our cameras. The proposed Convolutional Neural Network (CNN) cloud-based system was used to share computational resources for Artificial Neural Networks (ANN) to reduce redundant computation. The test system uses Internet of Things (IoT) services through our cameras system to capture the images and upload them to the Amazon Simple Storage Service (AWS S3) cloud. Then two detectors were running, Haar cascade and multitask cascaded convolutional neural networks (MTCNN), at the Amazon Elastic Compute (AWS EC2) cloud, after that the output results of these two detectors are compared using accuracy and execution time. Then the classified non-permission images are uploaded to the AWS S3 cloud. The validation accuracy of the offline augmentation face detection classification model reached 98.81%, and the loss and mean square error were decreased to 0.0176 and 0.0064, respectively. The execution time of all AWS cloud systems for one image when using Haar cascade and MTCNN detectors reached three and seven seconds, respectively.

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Clouds Height Classification Using Texture Analysis of Meteosat Images
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In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used

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Publication Date
Mon Jan 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Assessing Landsat Processing Levels and Support Vector Machine Classification
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The availability of different processing levels for satellite images makes it important to measure their suitability for classification tasks. This study investigates the impact of the Landsat data processing level on the accuracy of land cover classification using a support vector machine (SVM) classifier. The classification accuracy values of Landsat 8 (LS8) and Landsat 9 (LS9) data at different processing levels vary notably. For LS9, Collection 2 Level 2 (C2L2) achieved the highest accuracy of (86.55%) with the polynomial kernel of the SVM classifier, surpassing the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) at (85.31%) and Collection 2 Level 1 (C2L1) at (84.93%). The LS8 data exhibits similar behavior. Conv

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Publication Date
Thu Jan 01 2015
Journal Name
Applied And Computational Mathematics
Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Classification of Optical Images of Cervical Lymph Node Cells
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Abstract<p>the study considers the optical classification of cervical nodal lymph cells and is based on research into the development of a Computer Aid Diagnosis (CAD) to detect the malignancy cases of diseases. We consider 2 sets of features one of them is the statistical features; included Mode, Median, Mean, Standard Deviation and Maximum Probability Density and the second set are the features that consist of Euclidian geometrical features like the Object Perimeter, Area and Infill Coefficient. The segmentation method is based on following up the cell and its background regions as ranges in the minimum-maximum of pixel values. The decision making approach is based on applying of Minimum Dista</p> ... Show More
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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Publication Date
Tue Jul 31 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
Classification and monitoring of autism using svm and vmcm
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Autism is a lifelong developmental deficit that affects how people perceive the world and interact with each others. An estimated one in more than 100 people has autism. Autism affects almost four times as many boys than girls. The commonly used tools for analyzing the dataset of autism are FMRI, EEG, and more recently "eye tracking". A preliminary study on eye tracking trajectories of patients studied, showed a rudimentary statistical analysis (principal component analysis) provides interesting results on the statistical parameters that are studied such as the time spent in a region of interest. Another study, involving tools from Euclidean geometry and non-Euclidean, the trajectory of eye patients also showed interesting results. In this

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Scopus
Publication Date
Mon Mar 14 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Mathematical simulation of memristive for classification in machine learning
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Publication Date
Fri Dec 30 2022
Journal Name
College Of Islamic Sciences
Verses of cheerfulness and fluency of the face in the Holy Qur’an: An Objective Study
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Most of us are tired of the circumstances that surround us because of their deficiency, deprivation, and sullenness, even though troubles and pains are the soil in which the seeds of strong personality  sprout.             

   The content of the research is summed up in the fact that there is no need to frown, so let our face be free, and our word good and tolerant, so that we can be the most loving people of those who give them, and the Messenger of God (may God’s prayers and peace be upon him and his family) was known to be the heaviest  concerns  of people, but he was most smiling of people, by smiling, we buy lives, so we should get used to it, because that gives us hope and finds the world in our hands, an

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Transient response and performance of prestressed concrete deep T-beams with large web openings under impact loading
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Abstract<p>This study reports testing results of the transient response of T-shape concrete deep beams with large openings due to impact loading. Seven concrete deep beams with openings including two ordinary reinforced, four partially prestressed, and one solid ordinary reinforced as a reference beam were fabricated and tested. The effects of prestressing strand position and the intensity of the impact force were investigated. Two values for the opening’s depth relative to the beam cross-section dimensions were inspected under the effect of an impacting mass repeatedly dropped from different heights. The study revealed that the beam’s transient deflection was increased by about 50% with gre</p> ... Show More
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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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