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Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k dataset demonstrate superior performance compared to traditional methods, achieving higher accuracy, faster processing speed, and improved boundary preservation. Novelty: The proposed model effectively combines deep learning with fusion techniques, enhancing matting quality while maintaining robustness across various environmental conditions. Implications: These findings highlight the potential of integrating fusion techniques with deep learning for image matting, offering valuable insights for future research in automated image processing applications, including augmented reality, gaming, and interactive video technologies. Highlights:   Better Precision: Fusion techniques enhance fine detail preservation. Faster Processing: Lightweight U-Net improves speed and accuracy. Wide Applications: Useful for AR, gaming, and video processing.   Keywords: Deep image matting, computer vision, deep learning, fusion techniques, U-Net

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Image Compression Using Proposed Enhanced Run Length Encoding Algorithm
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In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm

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Publication Date
Wed May 31 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Satellite Image Mosaics Using Digital Cosine Transform (DCT) Descriptor
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In this research work, a modified DCT descriptor are presented to mosaics the satellite images based on Abdul Kareem [1] similarity criterion are presented, new method which is proposed to speed up the mosaics process is presented. The results of applying the modified DCT descriptor are compared with the mosaics method using RMSE similarity criterion which prove that the modified DCT descriptor to be fast and accurate mosaics method.

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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Analysing of Hueckel Edge Detector Performance Using Satellite Image
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In this research, an analysis for the standard Hueckel edge detection algorithm behaviour by using three dimensional representations for the edge goodness criterion is presents after applying it on a real high texture satellite image, where the edge goodness criterion is analysis statistically. The Hueckel edge detection algorithm showed a forward exponential relationship between the execution time with the used disk radius. Hueckel restrictions that mentioned in his papers are adopted in this research. A discussion for the resultant edge shape and malformation is presented, since this is the first practical study of applying Hueckel edge detection algorithm on a real high texture image containing ramp edges (satellite image).

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Publication Date
Fri Jan 01 2021
Journal Name
Cogent Engineering
Content-based image retrieval: A review of recent trends
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Publication Date
Mon May 27 2019
Journal Name
Al-academy
Advertising Image Semiotics in the Printed Poster: عبد الحسين عبد الواحد عبد الرزاق
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The present research aims at revealing the advertising image semiotics in the American printed poster by following the image's significance and its transformations through the poster design trends and indicating its nature whether it is an explicit or implicit image. The limits of the research were the American printed poster during 2016-2018 period. The theoretical side was determined by two sections, the first: (the advertising image semiotics) and the second (design trends in the printed poster). The research procedures were represented by the research method adopted in the analysis of the sample models identified in four models taken from the research community which contains (24) models. The selection was made according to the trend

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Publication Date
Wed Jan 10 2024
Journal Name
Annals Of Applied Sport Science
The Effect of an Electronic Device Designed to Measure the Knee Bending Angle in Developing the Skill of Catch and Clearance the High Ball for Football Goalkeepers
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Background. The use of modern aids and technology has contributed greatly to football development, the goalkeeper is the most important position in the team, and the use of devices gave objective readings about the goalkeeper's ability in terms of skill and physical aspects. Objectives. The research aimed to prepare exercises using an electronic device to measure the knee bending angle because of its great importance in developing the skill of catching and dimensions of the high ball for football goalkeepers. Methods. The researchers used the experimental method, and the sample consisted of (4) male goalkeepers under 15 years of age, one of the research procedures was to determine the biomechanical variables affecting the development of the

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Publication Date
Wed Feb 05 2020
Journal Name
Journal Of Physical Education
The Effect of Group Investigation Model on Learning overhead and underarm Pass in Volleyball
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Volleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app

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Publication Date
Sun Jan 01 2017
Journal Name
National Journal Of Physiology, Pharmacy And Pharmacology
The attitudes of final year medical and pharmacy students to interprofessional learning in Iraq
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Publication Date
Sun Jul 06 2014
Journal Name
Journal Of Educational And Psychological Researches
The influence of Online Training Courses on Iraqi EFL Instructors Teaching and Learning Process
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For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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