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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
Tue Jun 01 2021
Journal Name
Al-nahrain Journal Of Science
Medical Image Denoising Via Matrix Norm Minimization Problems
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This paper presents the matrix completion problem for image denoising. Three problems based on matrix norm are performing: Spectral norm minimization problem (SNP), Nuclear norm minimization problem (NNP), and Weighted nuclear norm minimization problem (WNNP). In general, images representing by a matrix this matrix contains the information of the image, some information is irrelevant or unfavorable, so to overcome this unwanted information in the image matrix, information completion is used to comperes the matrix and remove this unwanted information. The unwanted information is handled by defining {0,1}-operator under some threshold. Applying this operator on a given ma

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Publication Date
Mon Apr 17 2023
Journal Name
Wireless Communications And Mobile Computing
A Double Clustering Approach for Color Image Segmentation
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One of the significant stages in computer vision is image segmentation which is fundamental for different applications, for example, robot control and military target recognition, as well as image analysis of remote sensing applications. Studies have dealt with the process of improving the classification of all types of data, whether text or audio or images, one of the latest studies in which researchers have worked to build a simple, effective, and high-accuracy model capable of classifying emotions from speech data, while several studies dealt with improving textual grouping. In this study, we seek to improve the classification of image division using a novel approach depending on two methods used to segment the images. The first

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Scopus (4)
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Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Spin-Image Descriptors for Text-Independent Speaker Recognition
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Building a system to identify individuals through their speech recording can find its application in diverse areas, such as telephone shopping, voice mail and security control. However, building such systems is a tricky task because of the vast range of differences in the human voice. Thus, selecting strong features becomes very crucial for the recognition system. Therefore, a speaker recognition system based on new spin-image descriptors (SISR) is proposed in this paper. In the proposed system, circular windows (spins) are extracted from the frequency domain of the spectrogram image of the sound, and then a run length matrix is built for each spin, to work as a base for feature extraction tasks. Five different descriptors are generated fro

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Scopus (7)
Crossref (2)
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Publication Date
Tue Jan 07 2020
Journal Name
Xi,an University Of Architecture &technology
The Effect of Jigsaw strategy on Academic Achievement and Engagement in Learning among the 3rd male graders students in Chemistry
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The research aims to identify the effect of jigsaw strategy in learning achievement and engaging for the third grade intermediate students in chemistry. The research sample consisted of (61) students distributed in two experimental and control groups. The research tools consisted in the achievement test and the measure of engaging learning. The results showed that there are statistically significant differences at the level of (α = 0.05) between the experimental group and the control group in both the achievement test and the measure of learning involvement for the benefit of the experimental group. In this light, the researcher recommended the use of jigsaw strategy for teaching the subject matter. Lamia because of its impact in raising

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Publication Date
Tue Oct 25 2022
Journal Name
Minar Congress 6
HANDWRITTEN DIGITS CLASSIFICATION BASED ON DISCRETE WAVELET TRANSFORM AND SPIKE NEURAL NETWORK
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In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Investigation of Optimum Heat Flux Profile Based on the Boiling Safety Factor
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An experimental study is conducted to investigate the effect of heat flux distribution on the boiling safety factor of its cooling channel. The water is allowed to flow in a horizontal circular pipe whose outlet surface is subjected to different heat flux profiles. Four types of heat flux distribution profiles are used during experiments: (constant distribution profile, type a, triangle distribution profile with its maximum in channel center, type b, triangle distribution profile with its maximum in the channel inlet, type c, and triangle distribution profile with its maximum in the channel outlet, type d). The study is conducted using heat sources of (1000 and 2665W), water flow rates of (5, 7 and 9 lit/min). The water

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Publication Date
Tue Sep 18 2018
Journal Name
Kant
SOME METHODOLOGICAL OF LEARNING TENNIS STUDENTS
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This study is due to insufficient development of the issues of initial training in tennis at youthful (student) age. Objective: development of a methodological and scientific-methodological base of students' tennis with current trends in tennis. Summing up the best practices of modern tennis, we came to the conclusion that the formation of the art of reflection backhands in teaching beginner students of sports specialization to achieve future success. In modern conditions in the development of Russian tennis student opens the possibility of using new technologies and programs. Using these approaches, we have developed a training program and tested students' tennis in the pedagogical experiment, which resulted in its effectiveness.

Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
From Passive Learning to Critical Thinking
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Many Iraqi students are reluctant to actively participate in the English
language classroom. This reluctance is attributed to a number of factors, above which
is students' lack of thinking skills necessary to express their points of view. This
eventually results in passive learning, a real problem in English language learning in
Iraq.
A need for educational reforms and innovations seems essential. These involve
developing relevant teaching materials, adopting learner-centered approach,
promoting learner autonomy, and enhancing critical thinking.
This study is hoped to assist teachers of English to initiate change and foster
the expansion of thinking, and adopt various new strategies to increase classroom
par

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
From Passive Learning to Critical Thinking
...Show More Authors

Many Iraqi students are reluctant to actively participate in the English
language classroom. This reluctance is attributed to a number of factors, above which
is students' lack of thinking skills necessary to express their points of view. This
eventually results in passive learning, a real problem in English language learning in
Iraq.
A need for educational reforms and innovations seems essential. These involve
developing relevant teaching materials, adopting learner-centered approach,
promoting learner autonomy, and enhancing critical thinking.
This study is hoped to assist teachers of English to initiate change and foster
the expansion of thinking, and adopt various new strategies to increase classroom
par

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Publication Date
Thu Jun 30 2011
Journal Name
J Bagh College Dentistry
Comparison of the effect of stannous fluoride and sodium fluoride on surface roughness of Silorane and methacrylate based restorative material using light polarizing microscope
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Background: The high reactivity of hydrogen peroxide used in bleaching agents have raised important questions on their potential adverse effects on physical properties of restorative materials. The purpose of this in vitro study was to evaluate the effect of in-office bleaching agents on the microhardness of a new Silorane-based restorative material in comparison to methacrylate-based restorative material. Materials and method: Forty specimens of Filtek™ P90 (3M ESPE,USA) and Filtek™ Supreme XT (3M ESPE, USA) of (8mm diameter and 3m height) were prepared. All specimens were polished with Sof-Lex disks (3M ESPE, USA). All samples were rinsed and stored in incubator 37˚C for 24 hours in DDW. Ten sample of each material were subjected to

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