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The Effect of the Number of Key-Frames on the Facial Emotion Recognition Accuracy
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Key-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algorithm to select the best C-frames. The selected keyframes are then fed to a graph mining-based facial emotion recognition system to select the most effective sub-graphs in the given set of keyframes. Different experiments have been conducted using Surrey Audio-Visual Expressed Emotion (SAVEE) database and the results show that the proposed method can effectively capture the keyframes that give the best accuracy with a mean response time equals to 2.89.

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Publication Date
Fri Mar 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Accounting Thought Direction of Fair value on the Relevance: An Applied Study of a Sample of the Listed Banks Listed in the Iraqi Stock Exchange
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In accounting studies, more than one method is used to measure income and balance sheets elements. One of these methods is called the fair value, which use to determine the assets and liabilities ad it includes the benefits or self-satisfaction ability. This paper aims to focus on the importance of fair value as a basis of accounting measurement and its effects to achieve the relevant characteristics by using the equation is used by (Kythreotis) in his research, And Also , Editing this equation depending on the financial data and information of Iraqi Banks as a case.

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Publication Date
Wed Aug 01 2012
Journal Name
I-manger's Journal On Information Technology
A MODULE FOR ENHANCING RECOGNITION SYSTEM FOR QR CODE SCANNED IMAGE
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A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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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
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Tue Jun 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An efficient method for stamps recognition using Haar wavelet sub-bands
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Publication Date
Tue Aug 01 2023
Journal Name
Biomedical Signal Processing And Control
Decoding transient sEMG data for intent motion recognition in transhumeral amputees
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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing the impact of exchange rate fluctuations and inflation on the GDP in Iraq using the modern methodology of Cointegration for the period (1988-2020)
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     The research aims to analyze the impact of exchange rate fluctuations (EXM and EXN) and inflation (INF) on the gross domestic product (GDP) in Iraq for the period 1988-2020. The research is important by analyzing the magnitude of the macroeconomic and especially GDP effects of these variables, as well as the economic effects of exchange rates on economic activity. The results of the standard analysis using the ARDL model showed a long-term equilibrium relationship, according to the Bound Test methodology, from explanatory (independent) variables to the internal (dependent) variable, while the value of the error correction vector factor was negative and moral at a level less than (1%). The relationship bet

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Publication Date
Sun Jan 01 2012
Journal Name
Turkish Journal Of Physics
The influence of confinements on the photon flux spectra in amorphous silicon quantum dots
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
biofuels industry and impact on the development of the agricultural sector in developing countries
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Abstract

       Although the subject of biofuels industry is linked directly to the energy sector, but has links and numerous indirect effects, in particular effects on the environment and agriculture, this study (opportunities and challenges of biofuels industry and impact on the development of the agricultural sector in developing countries) a modest step to identify the industry in detail and identify the types of products and raw materials entering, then define or limit the positive and negative impacts of this industry in General and for specific products In particular, detailed, and then flip all those effects on the agricultural sector in developing countries can benef

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