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MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
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Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the skip connections are redesigned to give a more reliable fusion of features. MSRD-UNet allows aggregation of contextual information, and the network goes without needing to increase the number of parameters or required floating-point operations (FLOPS). The proposed model was evaluated on three multimodal datasets: polyp, skin lesion, and nuclei segmentation. The obtained results proved that the MSDR-Unet model outperforms several state-of-the-art U-Net-based methods.

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Luminance pyramid for image generation and colorization
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Many image processing and machine learning applications require sufficient image feature selection and representation. This can be achieved by imitating human ability to process visual information. One such ability is that human eyes are much more sensitive to changes in the intensity (luminance) than the color information. In this paper, we present how to exploit luminance information, organized in a pyramid structure, to transfer properties between two images. Two applications are presented to demonstrate the results of using luminance channel in the similarity metric of two images. These are image generation; where a target image is to be generated from a source one, and image colorization; where color information is to be browsed from o

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Publication Date
Wed Jul 25 2018
Journal Name
International Journal Of Engineering Trends And Technology
Fixed Predictor Polynomial Coding for Image Compression
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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Feature - Based Approach to Automatic Fixturing System Planning For Uniform Polyhedra Workpiece
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This paper demonstrates the design of an algorithm to represent the design stages of fixturing system that serve in increasing the flexibility and automation of fixturing system planning for uniform polyhedral part. This system requires building a manufacturing feature recognition algorithm to present or describe inputs such as (configuration of workpiece) and built database system to represents (production plan and fixturing system exiting) to this algorithm. Also knowledge – base system was building or developed to find the best fixturing analysis (workpiece setup, constraints of workpiece and arrangement the contact on this workpiece) to workpiece.

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
mathematical model for segmentation of the overall planning of puplic redemption company- ministry of industry and minerals
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Abstract

The study presents a mathematical model with a disaggregating approach to the problem of production planning of a fida Company; which belongs to the ministry of Industry. The study considers disaggregating the entire production into 3 productive families of (hydraulic cylinders, Aldblatt (dampers), connections hydraulics with each holds similar characteristics in terms of the installation cost, production time and stock cost. The Consequences are an ultimate use of the available production capacity as well as meeting the requirements of these families at a minimal cost using linear programming. Moreover, the study considers developing a Master production schedule that drives detailed material and production requi

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Wed Jun 30 2010
Journal Name
Al-kindy College Medical Journal
Evaluation the Effectiveness of Impregnated Net in Reducing Leishmaniasis Incidence: Diala-Iraq
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Background: Leishmaniasis is important public
health problem owing to its impact on morbidity
and mortality and difficulties in application of
effective control measures.
Objective: The aim of the study is to evaluate the
using of impregnate bed nets in the control of
leishmaniasis.
Methods: The study was conducted throughout
the years 2004 and 2005, in Diala Governorate
(about 60km north-east Baghdad). This is the first
study in Iraq for evaluation of the impregnated bed
net in control of leishmaniasis. Two villages were
selected to achieve this aim. The nets were
distributed for the first village to be used by their
population. The second village was served as
control.

Results: The

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Publication Date
Wed Mar 16 2022
Journal Name
2022 Muthanna International Conference On Engineering Science And Technology (micest)
Virtual Performance Evaluation of Net-Zero Energy Building (NZEB) Using BIM Analysis
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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Oxidative Coupling Reaction for Micro Trace Analysis of Mebendazol Residual with p-bromoaniline in Presence of n- bromosuccinimide
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Rapid, reproducible and accurate method has been developed for the assay for of mebendazol (MBZ) residual assay. The method is based on alkaline hydrolysis of MBZ with sodium hydroxide then oxidation with N-bromosuccinimide (NBS) followed by coupling with 4-Bromoaniline (4-BA) to yield a highly colored product absorbed at maximum 434 nm. Regression analysis of linearity range was found (0.6-2.8) µg.ml-1.  The optimum conditions that affect the oxidation were studied. The developed method was found to be precise with mean value of relative standard deviation (1.153- 1.303) and accurate with relative error (-0.5940-1.7821) .The calculated molar absorptivity and sandal sensitivity values of (29825 L.mol-1.cm-1), 0.0099 µg.cm-2 respe

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Oxidative Coupling Reaction for Micro Trace Analysis of Mebendazol Residual with p-bromoaniline in Presence of n- bromosuccinimide
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Rapid, reproducible and accurate method has been developed for the assay for of mebendazol (MBZ) residual assay. The method is based on alkaline hydrolysis of MBZ with sodium hydroxide then oxidation with N-bromosuccinimide (NBS) followed by coupling with 4-Bromoaniline (4-BA) to yield a highly colored product absorbed at maximum 434 nm. Regression analysis of linearity range was found (0.6-2.8) µg.ml-1.  The optimum conditions that affect the oxidation were studied. The developed method was found to be precise with mean value of relative standard deviation (1.153- 1.303) and accurate with relative error (-0.5940-1.7821) .The calculated molar absorptivity and sandal sensitivity values of (29825 L.mol-1.cm

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Using Statistical Methods to Increase the Contrast Level in Digital Images
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This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.

 

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