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
Excess molar volumes of five ternary mixtures of 2- methoxy ethanol(1) +butyl acetate(2)+benzene(3), +toluene(3), +chlorobenzene(3), +bromobenzene(3), and +nitrobenzene(3) have been measured at 303.15K. The excess molar volume exhibited positive deviation over the entire range of composition in the systems 2-methoxy ethanol(1)+ butyl acetate(2)+ benzene(3),+toluene(3) and sigmoid behavior in the case of the remaining systems. Flory's statistical theory have been extended to predict the excess molar volumes of the five ternary mixtures at 303.15 k over a wide range of composition . An excellent agreement has been found between the experimental and theoretical excess molar volumes , both in magnitude and sign .
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Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or
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The research tagged (the image of the soldier in contemporary Iraqi painting) dealt with the concept of the image as one of the basic concepts in the creative achievement, whether it is in the field of art, literature or beauty. Therefore, the concept of the image expanded to express the various aspects of human creativity, including the field of painting. To know the image of the soldier in contemporary Iraqi painting, the research included four chapters. The first chapter focused on the methodological framework of the research, while the second chapter included three sections. The first topic dealt with the philosophical and artistic concept of the image. The second topic was concerned with the representations of the soldier's image in
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The research aims mainly to the role of the statement style costs on the basis of activity based on performance (PFABC) to reduce production cost and improve the competitive advantage of economic units and industrial under the modern business environment dominated by a lot of developments and changes rapidly, which necessitates taking them and criticize them to ensure survival and continuity. The research problem is the inability of traditional cost methods of providing useful information to the departments of units to take many administrative decisions, particularly decisions related to the product and calculating the costs of the quality of the sound and the availability of the need and the ability to replace methods capa
... Show MoreThe designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
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