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
Objective: This study evaluated the effect of immediate dentin sealing on the marginal adaptation of lithium disilicate overlays with three different types of resin-luting agents: preheated composite, dual-cure adhesive resin, and flowable composite. Materials and Methods: Forty-eight maxillary first premolars of similar size were prepared with a butt joint preparation design. The teeth were separated into two primary groups, each with twenty-four teeth: Group DDS: Delay dentin sealing (non-IDS) teeth were not treated. Group IDS: dentin sealing was applied immediately after teeth preparation. Each group was subsequently separated into three separate subgroups. Subgroups (DDS+Phc, IDS+Phc): cemented with preheated composite (Enamel plus HRi,
... Show MoreShallow foundations are usually used for structures with light to moderate loads where the soil underneath can carry them. In some cases, soil strength and/or other properties are not adequate and require improvement using one of the ground improvement techniques. Stone column is one of the common improvement techniques in which a column of stone is installed vertically in clayey soils. Stone columns are usually used to increase soil strength and to accelerate soil consolidation by acting as vertical drains. Many researches have been done to estimate the behavior of the improved soil. However, none of them considered the effect of stone column geometry on the behavior of the circular footing. In this research, finite ele
... Show MoreWith the great development in the field of the Internet, the talk about the new media and its implications began, And its interactive services have made the future of media material sometimes participating in it and manufacturing it at other times,
the public is seeking information and choosing the appropriate ones, as well as exchanging messages with the sender after what the role of the receiver is just receiving information only.
This study aims to demonstrate the effects of using digital media in various forms and types to construct the value system of Iraqi society through the identification of the following aims:
Identify the most popular digital media for the Iraqi public in their daily lives on the Internet.
Identify
Praise be to God, Lord of the Worlds, and prayers and peace be upon the most honorable of creation, Muhammad, whom God sent as a mercy to the worlds, and his pure God and his faithful companions. The Islamic heritage was replete with texts issued from among the pure infallibility, which constituted a prominent teacher that takes the student to stop there in search of its goals, purposes and beauty. The choice was made from those texts that were issued by the imams of Muslims in the Abbasid era, namely Imam Muhammad al-Jawad, his son Imam Ali al-Hadi and his grandson Imam Hassan Zaki al-Askari. (Peace be upon them), and scholars have called them (sons of satisfaction), and researchers have shed light on these texts from rhetorical, artistic
... Show MoreThis research sheds light on the development that has occurred on the use of press pictures in the Iraqi press by analyzing the form and content of the images used in (Al-Sabaah) newspaper for the 2012 model. The researcher's interest in this topic for what represented by the press picture of a way to highlight and attract the reader's attention to the substance journalist who represents the goals behind the newspaper publishing.
This research is divided into three sections. The first one dealt with the methodological framework of the research, and the second part addressed the aspect of press pictures and its history and technological development, while the third section devoted to the study of the development of the form and co
... Show MoreIn this paper we investigate the automatic recognition of emotion in text. We propose a new method for emotion recognition based on the PPM (PPM is short for Prediction by Partial Matching) character-based text compression scheme in order to recognize Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method is very effective when compared with traditional word-based text classification methods. We have also found that our method works best if the sizes of text in all classes used for training are similar, and that performance significantly improves with increased data.
The petroleum industry, which is one of the pillars of the national economy, has the potential to generate vast wealth and employment possibilities. The transportation of petroleum products is complicated and changeable because of the hazards caused by the corrosion consequences. Hazardous chemical leaks caused by natural disasters may harm the environment, resulting in significant economic losses. It significantly threatens the aim for sustainable development. When a result, determining the likelihood of leakage and the potential for environmental harm, it becomes a top priority for decision-makers as they develop maintenance plans. This study aims to provide an in-depth understanding of the risks associated with oil and gas pipeli
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