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
Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no
... Show MoreEnhancement of the performance for hybrid solar air conditioning system was presented in this paper. The refrigerant temperature leaving the condenser was controlled using three-way valve, this valve was installed after the compressor to regulate refrigerant flow rate towards the solar system. A control system using data logger, sensors and computer was proposed to set the opening valve ratio. The function of control program using LabVIEW software is to obtain a minimum refrigerant temperature from the condenser outlet to enhance the overall COP of the unit by increasing the degree of subcooled refrigerant. A variable load electrical heater with coiled pipe was used instead of the solar collector and the storage tank to simulate the sola
... Show More: In modern optical communication system, noise rejection multiple access interference (MAI) must be rejected in dense access network (DAN). This paper will study the dual optical band pass and notch filters. They will be extracted with tunable FWHM using 10cm (PMF) with different cladding diameters formed with etching 125μm PMF after immersing it with 40% of hydrofluoric acid (HF). This fiber acts as assessing fiber to perform Sagnac interferometer with splicing regions that placed 12cm (SMF) for performing hybrid Sagnac interferometer that consists of Mach-Zehnder instead of Sagnac loop which is illuminated by using laser source with centroid wavelength of 1546.7nm and FWHM of 286 pm or 9 ns in the time domain. . Firs
... Show MoreThe increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.
<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121
... Show MoreThis investigation aims to study some properties of lightweight aggregate concrete reinforced by mono or hybrid fibers of different sizes and types. In this research, the considered lightweight aggregate was Light Expanded Clay Aggregate while the adopted fibers included hooked, straight, polypropylene, and glass. Eleven lightweight concrete mixes were considered, These mixes comprised of; one plain concrete mix (without fibers), two reinforced concrete mixtures of mono fiber (hooked or straight fibers), six reinforced concrete mixtures of double hybrid fibers, and two reinforced concrete mixtures of triple hybrid fibers. Hardened concrete properties were investigated in this study. G
This investigation aims to study some properties of lightweight aggregate concrete reinforced by mono or hybrid fibers of different sizes and types. In this research, the considered lightweight aggregate was Light Expanded Clay Aggregate while the adopted fibers included hooked, straight, polypropylene, and glass. Eleven lightweight concrete mixes were considered, These mixes comprised of; one plain concrete mix (without fibers), two reinforced concrete mixtures of mono fiber (hooked or straight fibers), six reinforced concrete mixtures of double hybrid fibers, and two reinforced concrete mixtures of triple hybrid fibers. Hardened concrete properties were investigated in this study. G
High peak to average power ration (PAPR) in orthogonal frequency division multiplexing (OFDM) is an important problem, which increase the cost and complexity of high power amplifiers. One of the techniques used to reduce the PAPR in OFDM system is the tone reservation method (TR). In our work we propose a modified tone reservation method to decrease the PAPR with low complexity compared with the conventional TR method by process the high and low amplitudes at the same time. An image of size 128×128 is used as a source of data that transmitted using OFDM system. The proposed method decrease the PAPR by 2dB compared with conventional method with keeping the performance unchanged. The performance of the proposed method is tested with
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