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Development of Iraqi License Plate Recognition System based on Canny Edge Detection Method
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the road in all the sections of the country. Vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the developing system is consist of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny Edge detection algorithm, Connect Component Analysis (CCA) have been exploited for segmenting characters. Finally, a Multi-Layer Perceptron Artificial Neural Network (MLPANN) model is utilized to recognize and detect the vehicle license plate characters, and hence the results are displayed as a text on GUI. The proposed system successfully identified and recognized multi_style Iraqi license plates using different image situations and it was evaluated based on different metrics performance, achieving an overall system performance of 91.99%. This results shows the effectiveness of the proposed method compared with other existing methods, whose average recognition rate is 86% and the average processing time of one image is 0.242s which proves the practicality of the proposed method.

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Publication Date
Fri Jan 01 2016
Journal Name
International Journal Of Advanced Computer Science And Applications
Face Detection and Recognition Using Viola-Jones with PCA-LDA and Square Euclidean Distance
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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
A Recognition System for Subjects' Signature Using the Spatial Distribution of Signature Body
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This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s

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Publication Date
Wed Jul 01 2020
Journal Name
2020 42nd Annual International Conference Of The Ieee Engineering In Medicine & Biology Society (embc)
Recurrent Fusion of Time-Domain Descriptors Improves EMG-based Hand Movement Recognition
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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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Publication Date
Tue Jan 01 2019
Journal Name
Cogent Engineering
IEC 60909 and ANSI standards comparison with ASCC based fault calculations of Iraqi power system
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Developing of bacterial mutagenic assay system for detection
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Been Antkhav three isolates of soil classified as follows: Bacillus G3 consists of spores, G12, G27 led Pal NTG treatment to kill part of the cells of the three isolates varying degrees treatment also led to mutations urged resistance to streptomycin and rifampicin and double mutations

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
A Sociocultural Perspective on Iraqi EFL Learners Reading Comprehension Development
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 Improving speaking skills of Iraqi EFL students was the main purpose of the current research. Thirty EFL students were selected as the research participants for achieving this aim. All students completed the pretest and then spent the next 25 weeks meeting for 90 minutes each to present their nine lectures, answer difficult questions, and get feedback on their use of language in context. Progressive-tests, posttests and delayed post-tests followed every three courses. The researcher utilized SPSS 22 to anal Analyze the data descriptively and inferentially after doing an ANOVA on repeated measurements. It has been shown that using the ideas of sociocultural theory in the classroom has an important and positive impact on students of

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Publication Date
Mon Nov 10 2025
Journal Name
2025 18th International Conference On Development In Esystem Engineering (dese)
Arrhythmia Recognition Algorithm Using Squared Krawtchouk-Tchebichef Polynomial-Based Feature Extraction
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Fri Feb 05 2021
Journal Name
Research In Intelligent And Computing In Engineering
Implementing Web Testing System Depending on Performance Testing Using Load Testing Method.
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Web testing is very important method for users and developers because it gives the ability to detect errors in applications and check their quality to perform services to users performance abilities, user interface, security and other different types of web testing that may occur in web application. This paper focuses on a major branch of the performance testing, which is called the load testing. Load testing depends on an important elements called request time and response time. From these elements, it can be decided if the performance time of a web application is good or not. In the experimental results, the load testing applied on the website (http://ihcoedu.uobaghdad.edu.iq) the main home page and all the science departments pages. In t

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