Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for de-noising noisy CCTV images. Data-store is used tomanage our dataset, which is an object or collection of data that are huge to enter in memory, it allows to read, manage, and process data located in multiple files as a single entity. The CAN architecture provides integral deep learning layers such as input, convolution, back normalization, and Leaky ReLu layers to construct multi-scale. It is also possible to add custom layers like adaptor normalization (µ) and adaptive normalization (Lambda) to the network. The performance of the developed CAN approximation operator on the bilateral filtering noisy image is proven when improving both the noisy reference image and a CCTV foggy image. The three image evaluation metrics (SSIM, NIQE, and PSNR) evaluate the developed CAN approximation visually and quantitatively when comparing the created de-noised image over the reference image.Compared with the input noisy image, these evaluation metrics for the developed CAN de-noised image were (0.92673/0.76253, 6.18105/12.1865, and 26.786/20.3254) respectively
In this paper, a fast lossless image compression method is introduced for compressing medical images, it is based on splitting the image blocks according to its nature along with using the polynomial approximation to decompose image signal followed by applying run length coding on the residue part of the image, which represents the error caused by applying polynomial approximation. Then, Huffman coding is applied as a last stage to encode the polynomial coefficients and run length coding. The test results indicate that the suggested method can lead to promising performance.
Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
... Show MoreThe regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influenc
... Show MoreIncremental sheet metal forming process is an advanced flexible manufacturing process to produce various 3D products without using dedicated tool as in conventional metal forming. There are a lot of process parameters that have effect on this process, studying the effect of some parameters on the strain distributions of the product over the length of deformation is the aim of this study.
In order to achieve this goal, three factors (tool forming shape, feed rate and incremental step size) are examined depending on three levels on the strain distributions over the wall of the product. Strain measurement was accomplished by using image processing technique using MATALB program. The significance of the control factors are explored u
... Show MoreThe research discusses the mechanism for analyzing the salary scale in the public sector through an analysis of grades, their stages, occupants and their financial entitlements, and the extent to which the information obtained for their investment in strategic planning, conducting correction and treatment can be used. The salaries of the employees in them, whose number is (1117) employees, to be a field of research, as the salary structure in it for the year 2019 was analyzed by relying on a number of statistical tools in the analysis process, including the arithmetic circles, upper limits, minimum limits and percentage, and with
... Show MoreSewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.
In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage
... Show MoreNanofertilizers offer a promising solution to increase crop yields amid increasing population pressure. Yet there have been safety concerns about their use, particularly in challenging conditions. This work was designed to assess the toxicological effects of a chelated multi-micronutrient nanofertilizer on albino rats (Rattus norvegicus) as non-target organisms, focusing on the liver, which has important metabolic functions. Thirty-five animals were weighed and randomly divided into 5 groups (n=7). A negative control group was included, and four experimental groups (C1-C4) were given the test item. The dosing regimen for the experimental groups was 15 oral doses of nanofertilizer every other day for 29 days. All the groups were
... Show MoreThe research aims to: build and record a measure of cognitive participation among second-year female students at the College of Physical Education and Sports Sciences, University of Baghdad. The researchers used the descriptive approach in the survey style for the research sample. The sample was selected from female students and divided into: (10) female students for the survey sample, and (80) female students for the construction and codification sample. The data were statistically analyzed by the researchers using SPSS, the T-test for independent and correlated samples, Pearson's simple correlation coefficient, Cronbach's alpha, Chi-square, and Spearman-Brown. They were recruited for the samples. The study concluded that constr
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