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Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eyes' observation of the different colors and features of images. We propose a multi-layer hybrid system for deep learning using the unsupervised CAE architecture and using the color clustering of the K-mean algorithm to compress images and determine their size and color intensity. The system is implemented using Kodak and Challenge on Learned Image Compression (CLIC) dataset for deep learning. Experimental results show that our proposed method is superior to the traditional compression methods of the autoencoder, and the proposed work has better performance in terms of performance speed and quality measures Peak Signal To Noise Ratio (PSNR) and Structural Similarity Index (SSIM) where the results achieved better performance and high efficiency With high compression bit rates and low Mean Squared Error (MSE) rate the results recorded the highest compression ratios that ranged between (0.7117 to 0.8707) for the Kodak dataset and (0.7191 to 0.9930) for CLIC dataset. The system achieved high accuracy and quality in comparison to the error coefficient, which was recorded (0.0126 to reach 0.0003) below, and this system is onsidered the most quality and accurate compared to the methods of deep learning compared to the deep learning methods of the autoencoder

Publication Date
Fri Jan 01 2010
Journal Name
Thesis
Design and Implementation proposed Encoding and Hiding Text in an Image
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NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4

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Publication Date
Sun Dec 11 2022
Journal Name
Journal Of The College Of Basic Education
Breaking the Stereotype Image of Women in Caryl Churchill’s Top Girls
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تحلل الورقة الحالية تمثيل كاريل تشرشل للصورة النمطية للمرأة في Top Girls (1982). تُظهر المسرحية كيف وصلت النساء في نضالهن لمحاربة اضطهاد الرجال عبر التاريخ ، إلى مستوى من القوة والحرية يستخدمان للسيطرة على جنسهن دون شفقة. مارلين ، الشخصية المركزية في هذه المسرحية ، هي امرأة تبنت الصفات الذكورية إلى أقصى الحدود. لتسلق سلم النجاح إلى قمته ، تضحي مارلين بطفلها وعائلتها وحبها. كما تعرض المسرحية النساء الصامتات والم

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Publication Date
Fri Sep 30 2022
Journal Name
Nasaq Journal
The Demonic Image of Autoimmunity in Dan Brown's Angels and Demons
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Autoimmunity is a philosophical term that enhances the fields of life-sciences, and links out to the unnatural behaviour of an individual. It is caused by the defenses of an organism that deceive its own tissues. Obviously, the immune system should protect the body against invading cells with types of white blood cells called antibodies. Nevertheless, when an autoimmune disease attacks, it causes perilous actions like suicide. Psychologically, Jacques Derrida (1930-2004) calls autoimmunity a double suicide, because it harms the self and the other. In this case, the organ disarms betraying cells, as the immune system cannot provide protection. From a literary perspective, Derrida has called autoimmunity as deconstruction for over forty years

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Publication Date
Mon Jun 30 2025
Journal Name
مجلة ميسان للدراسات الاكاديمية
The poetic image in the Diwan of Al-Oqaisher Al-Asadi
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Publication Date
Thu Feb 15 2024
Journal Name
Evolving Systems
Boosted Aquila Arithmetic Optimization Algorithm for multi-level thresholding image segmentation
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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Sat Apr 01 2017
Journal Name
Al–bahith Al–a'alami
Stereotypical Frames if the Image of Women in the Iraqi TV Drama after 2003
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This study aims to deliver the woman’s image and to unveil on how to be introduced in the TV series. The research is based on the survey method-using content analysis tool. The research sample represented in the TV series produced by the IMN, which were displayed in 2014 and used the pattern of Margaret Gallagher to analyze the content of the series in accordance with the frame analysis theory.
The study came up with declination of the woman’s representation compared with man in Iraqi TV drama, also the study finds that the series introduced the woman according to the personal, social, political, and economic frames in a standardizing method. It focuses on the characteristics always attributed to it as showing her obedient of the

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Publication Date
Tue Jan 10 2017
Journal Name
International Journal Of Dynamics And Control
On local approximation-based adaptive control with applications to robotic manipulators and biped robots
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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Scopus (16)
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