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Synthetic Aperture Radar Image Classification: a Survey: Survey

In this review paper, several studies and researches were surveyed for assisting future researchers to identify available techniques in the field of classification of Synthetic Aperture Radar (SAR) images. SAR images are becoming increasingly important in a variety of remote sensing applications due to the ability of SAR sensors to operate in all types of weather conditions, including day and night remote sensing for long ranges and coverage areas. Its properties of vast planning, search, rescue, mine detection, and target identification make it very attractive for surveillance and observation missions of Earth resources.  With the increasing popularity and availability of these images, the need for machines has emerged to enhance the ability to identify and interpret these images effectively. This is due to the fact that SAR image processing requires the formation of an image from the measured radar scatter returns, followed by a treatment to discover and define the image's composition. After reviewing several previous studies that succeeded in achieving a classification of SAR images for specific goals, it became obvious that they could be generalized to all types of SAR images. The most prominent use of Convolutional Neural Networks (CNN) was successful in extracting features from the images and training the neural network to analyze and classify them into classes according to these features. The dataset used in this model was obtained from the Moving and Stationary Target Acquisition and Recognition (MSTAR) database, which consists of a set of SAR images of military vehicles, for which the application of the CNN approach achieved a final accuracy of 97.91% on ten different classes.

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Publication Date
Sun Mar 13 2011
Journal Name
Baghdad Science Journal
Some A Survey Study On The Role of Women in Controlling Parasites Contaminated with Vegetables.

Three hundred samples of washing water of vegetables were collected from women aged ( 15- 6o) years from different area in Baghdad governorate and its suburbs include two rural area ( Jaddria in Baghdad university and Al –Wagif in Rashdia) and two urbane area (Mansoure and Escan) . The samples were examined by precipitation method and then by staining method ( Lugols –Iodine stain) . The percentage of infection of intestinal parasites 36.3% include 15.3% for urban area and 57.3% in rural area and a significant difference was found between those groups . .The results showed also increased in the prevalence of parasitic infection in group age (15 -30) year .Also the results showed only 109 sample infected with eight specie

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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

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
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Workplace Respect on Employee Performance: A Survey Study in Abu Ghraib Dairy Factory

This paper aims to explain the effect of workplace respect on employee performance at Abu Ghraib Dairy Factory (AGDF). For achieving the research aim, the analytical and descriptive approach was chosen using a questionnaire tool for collecting data.  It covers 22 items; ten of them for the workplace respect variable and twelve items for the employee performance variable. The research population involved human resources who work at AGDF in Baghdad within two administrative levels (top and middle). We conducted a purposive stratified sample approach. It was distributed 70 questionnaire forms, and 65 forms were received. However, six of them had missing data and did not include in the final data analysis. The main results are t

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Satellite image classification using proposed singular value decomposition method

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Satellite Image Classification using Spectral Signature and Deep Learning

    When images are customized to identify changes that have occurred using techniques such as spectral signature, which can be used to extract features, they can be of great value. In this paper, it was proposed to use the spectral signature to extract information from satellite images and then classify them into four categories. Here it is based on a set of data from the Kaggle satellite imagery website that represents different categories such as clouds, deserts, water, and green areas. After preprocessing these images, the data is transformed into a spectral signature using the Fast Fourier Transform (FFT) algorithm. Then the data of each image is reduced by selecting the top 20 features and transforming them from a two-dimensiona

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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Survey of some Fish Species from Different Localities in Baghdad
Abstract<p>This study is concerned with a survey of seven species belonging to seven genera under two families and two orders found in some different areas of the Tigris River, especially since these areas have not been surveyed for a long time, and an attempt to identify the existing species at the present time after the recent water scarcity of the Tigris and Euphrates rivers and all water bodies interior of Iraq and the impact of this scarcity on the fish diversity found in some areas of the Tigris River in Baghdad.</p>
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
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Publication Date
Tue Dec 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
SURVEY AND UPDATING CHECKLIST OF DIPTERAN SPECIES WITH FORENSIC IMPORTANCE

In the present investigation, 24 adult dipteran species with forensic importance belonging to 13 genera and 8 families that were collected from different localities of Iraq. The specimens were identified by different taxonomical keys; in addition the date and localities of collecting specimens were recorded.

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Publication Date
Sun Feb 06 2022
Journal Name
Iraqi Journal Of Science
Survey Study on the Prevalence of Cutaneous Leishmaniasis in Iraq

Human cutaneous leishmaniasis (CL) is caused by Leishmania sp. parasite and endemic in Iraq. The current study was including analysis of available database from Iraqi CDC to determine the distribution of CL cases for the period (2008-2015 years) in Iraq. Total reported cases for this period were 17001 (range 2.9-10.5 per 100,000 individuals). Highest reported cases were recorded in the year 2015 (4000 cases). Male infections cases of CL (50.8%) were more than female infections (49.2%). Highest infections of CL were observed in the age group (5-14yr.) as (34.6%), While the lowest infection of CL were observed in the age group (>1yr.) as (4.3%). Highest infection case of CL was observed in the middle and west of Iraq (53%). In contrast,

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Survey of Keratinophilic Fungi in the Tigris River in Baghdad

The present study includs the isolation and identification of Keratinophilic fungi in fresh water samples collected from Tigris river in Baghdad, Iraq. Samples were collected from different districts of Baghdad (Al-Rustumia, Madina Al-Teb, Al-Azamia, Al-Kadimia, Al-Dorha and Al-Kanah). The water samples were examined for keratinophilic fungi by the plating method culturing and Hair Baiting Technique. A total number of 18 genera are recorded, in which the Tigris water indicates an impressive diversity of fungi. A variety of fungal strains were isolated from river water, out of 814 fungal colonies, Aspergillus terrus (5.5%) was the most frequent species, followed by Asperg

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