Preferred Language
Articles
/
Vha2ZIkBVTCNdQwCSYkW
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
...Show More Authors

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

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Mar 05 2021
Journal Name
Materials
Optimum Placement of Heating Tubes in a Multi-Tube Latent Heat Thermal Energy Storage
...Show More Authors

Utilizing phase change materials in thermal energy storage systems is commonly considered as an alternative solution for the effective use of energy. This study presents numerical simulations of the charging process for a multitube latent heat thermal energy storage system. A thermal energy storage model, consisting of five tubes of heat transfer fluids, was investigated using Rubitherm phase change material (RT35) as the. The locations of the tubes were optimized by applying the Taguchi method. The thermal behavior of the unit was evaluated by considering the liquid fraction graphs, streamlines, and isotherm contours. The numerical model was first verified compared with existed experimental data from the literature. The outcomes re

... Show More
View Publication Preview PDF
Scopus (17)
Crossref (18)
Scopus Clarivate Crossref
Publication Date
Tue Feb 01 2011
Journal Name
Iop Conference Series: Materials Science And Engineering
Contour extraction of echocardiographic images based on pre-processing
...Show More Authors

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

View Publication Preview PDF
Scopus (2)
Scopus Clarivate Crossref
Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
...Show More Authors

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 More
View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Use of Infrared Light to Improve Breast Sonographic images
...Show More Authors

It is well known that sonography is not the first choice in detecting early breast tumors. Improving the resolution of breast sonographic image is the goal of many workers to make sonography a first choice examination as it is safe and easy procedure as well as cost effective. In this study, infrared light exposure of breast prior to ultrasound examination was implemented to see its effect on resolution of sonographic image. Results showed that significant improvement was obtained in 60% of cases.

View Publication Preview PDF
Crossref
Publication Date
Fri May 17 2013
Journal Name
International Journal Of Computer Applications
Fast Lossless Compression of Medical Images based on Polynomial
...Show More Authors

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.

View Publication Preview PDF
Crossref (7)
Crossref
Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Effect of laser process an inclined surface cutting of mild steel then analysis data statistically by RSM
...Show More Authors

The 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 More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Wed Mar 13 2019
Journal Name
Al-khwarizmi Engineering Journal
Investigation the Effect of Process Variables on the Formability of Parts Processed by Single Point Incremental Forming
...Show More Authors

Incremental 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 More
View Publication Preview PDF
Crossref
Publication Date
Thu Dec 01 2016
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
FIRST RECORD OF NIGRA SCALE, PARASAISSETIA NIGRA (NIETNER, 1861) (HEMIPTERA; COCCIDAE) AS A PEST OF FIG TREES IN IRAQ
...Show More Authors

     The nigra scale, Parasaissetia nigra (Nietner, 1861) (Hemiptera, Coccidae) recorded as a new insect pest attacking fig trees, Ficus carica (Moraceae) in Iraq. It was observed during April 2014 in residential garden at Al-Hurriyah district in Baghdad.

View Publication Preview PDF
Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Estimation of secondary compounds content of some citrus leaves and their relationship by dietary preference for yellow scale insect Aonidiella. Orientalis (Hemiptera: Diaspididae)
...Show More Authors
Abstract<p>The yellow scale insect <italic>Aonidiella orientalis</italic> is an important pest of citrus trees as it absorbs sap from leaves and fruits, causing leaves to turn yellow and deform fruits and drop them. The results of study showed nutritional preference of the insect over some of studied citrus species, as sour orange was the most preferred, followed by lemon and grapefruit, mandarin and oranges were least preferred, with a rate of 22.3, 13.3, 11.7, 10.8, 3.9, and insect / 2 inch<sup>2</sup>, respectively. while results showed a difference in the content of citrus leaves from the secondary compounds, with highest concentration of phenols and total flavonoids in o</p> ... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Estimation of Heavy Metals Contamination in the Soil of Zaafaraniya City Using the Neural Network
...Show More Authors

View Publication
Scopus (6)
Crossref (2)
Scopus Clarivate Crossref