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Accurate license plate recognition system for different styles of Iraqi license plates
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Automatic license plate recognition (ALPR) used for many applications especially in security applications, including border control. However, more accurate and language-independent techniques are still needed. This work provides a new approach to identifying Arabic license plates in different formats, colors, and even including English characters. Numbers, characters, and layouts with either 1-line or 2-line layouts are presented. For the test, we intend to use Iraqi license plates as there is a wide range of license plate styles written in Arabic, Kurdish, and English/Arabic languages, each different in style and color. This variety makes it difficult for recent traditional license plate recognition systems and algorithms to recognize all these license plate types using the same algorithm. In this work, a new method has been proposed to efficiently recognize all these types of license plates. This has been done by utilizing a series of algorithms for preprocessing and recognition with new identification strategies. The results show that the system recognized license plate numbers with higher accuracy, reaching up to 97.85%. However, the method field to detect license plates when there are some high deformations in plate numbers or when they are partially covered with mud, which makes it difficult to distinguish numbers.

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Publication Date
Mon Aug 01 2022
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Dorsal hand veins features extraction and recognition by correlation coefficient
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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date
Fri Aug 16 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Publication Date
Fri Apr 02 2021
Journal Name
New Trends In Information And Communications Technology Applications: 4th International Conference, Ntict 2020, Baghdad, Iraq, June 15, 2020, Proceedings 4
Iris recognition using localized Zernike features with partial iris pattern
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Publication Date
Sat Jan 01 2022
Journal Name
Ieee Access
Hand Gesture Recognition With Acoustic Myography and Wavelet Scattering Transform
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Publication Date
Fri Jul 01 2011
Journal Name
Engineering And Technology Journal
Off-Line Arabic Signature Recognition Based on Invariant Moments Properties
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Publication Date
Sun Jun 07 2015
Journal Name
Baghdad Science Journal
On The Nearby-Tip Strain Investigation and Failure-Propability Evaluation for Impacted Thin Plates Using the 2-Random-Variables Multi-Canonical-Based Joint Propability Distributions
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The study of the validity and probability of failure in solids and structures is highly considered as one of the most incredibly-highlighted study fields in many science and engineering applications, the design analysts must therefore seek to investigate the points where the failing strains may be occurred, the probabilities of which these strains can cause the existing cracks to propagate through the fractured medium considered, and thereafter the solutions by which the analysts can adopt the approachable techniques to reduce/arrest these propagating cracks.In the present study a theoretical investigation upon simply-supported thin plates having surface cracks within their structure is to be accomplished, and the applied impact load to the

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Different Methods for Estimating Location Parameter & Scale Parameter for Extreme Value Distribution
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      In this study, different methods were used for estimating location parameter  and scale parameter for extreme value distribution, such as maximum likelihood estimation (MLE) , method of moment  estimation (ME),and approximation  estimators based on percentiles which is called white method in estimation, as the extreme value distribution is one of exponential distributions. Least squares estimation (OLS) was used, weighted least squares estimation (WLS), ridge regression estimation (Rig), and adjusted ridge regression estimation (ARig) were used. Two parameters for expected value to the percentile  as estimation for distribution f

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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
Tue Nov 01 2016
Journal Name
Expert Systems With Applications
Combined influence of forearm orientation and muscular contraction on EMG pattern recognition
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