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Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN, YOLO, and SSD for effective drone detection in various environments. We have found that both Faster RCNN and YOLO have high recognition ability compared to SSD; on the other hand, SSD has good detection ability.

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Publication Date
Sun Aug 03 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Quantitative detection and correlation of Epstein - Barr Virus in plasma with gingivitis and severity of chronic periodontitis by using real-time polymerase chain reaction technique
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Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),

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Publication Date
Fri Dec 01 2023
Journal Name
Iranian Journal Of Medical Microbiology
Detection of Biologically Active Compounds in <i>Eriobotrya japonica</i> L. Seeds Extract and Determination of Their Effectiveness Against Dermatophytes
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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The Degree of Difficulties in Learning Mathematics for the Fifth and Sixth Grades from the Teachers' Point of View and Their Suggestions for Addressing Them
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The current study aimed to identify the difficulties faced by the student in mathematics and possible proposals to address these difficulties. The study used a descriptive method also used the questionnaire to collect data and information were applied to a sample of (163) male and female teachers. The results of the study found that the degree of difficulties in learning mathematics for the fifth and sixth grades is high for some paragraphs and intermediate for other paragraphs, included the student's field. The results also revealed that there were no statistically significant differences at the level of significance (α = 0.05) between the responses of the members of the study sample from male and female teachers to the degree of diffi

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Publication Date
Sun Aug 15 2021
Journal Name
Al-qadisiyah Journal Of Pure Science Vol.(26) Issue (special Issue Num.4) (2021) Pp. 27–30
Cyclic partition for the groups of (2,41) and (2,43)
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Publication Date
Thu Jun 15 2023
Journal Name
Journal Of Population Therapeutics And Clinical Pharmacology
Detection the Phylogenetic groups of E. coli that isolated from diarrheal in children under five years and study their relationship of common serotypes in Baghdad hospitals.
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Publication Date
Tue Jun 30 2020
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF HEAVY METALS POLLUTION INTYPES OF MILK SAMPLES IN BAGHDAD MARKETS: DETECTION OF HEAVY METALS POLLUTION INTYPES OF MILK SAMPLES IN BAGHDAD MARKETS
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The levels of lead (pb), copper (cu), cobalt (co) and cadmium (cd) were determined in different kinds of milk and the health risks were evaluated. The mean levels were 0.73±0.21, 0.06±0.01, 0.12±0.01 and 0.14±0.01 ppm for these metals respectively. The levels of pb and cu were found to be insignificant differences (p<0.05), whereas the levels of co and cd, were no significant differences (p>0.05). The dry and liquid kinds of milk were different significantly (p<0.05), whereas the original, was no significant differences (p>0.05). The values for all metals were more than one. The metals pb and cd were detected at highest concentrations in most dry and liquid milk samples.

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Publication Date
Tue Sep 06 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
DETECTION OF IRON AVAILABITITY OF WHEAT FLOUR PRODUCED IN BAGHDAD CITY MILLS: DETECTION OF IRON AVAILABITITY OF WHEAT FLOUR PRODUCED IN BAGHDAD CITY MILLS
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In the present study, a total of 245 flour samples were collected from 49 mills on both sides of Baghdad city (Al- Karkh and Al- Resafa), during the period from 1/6 - 1/12/ 2015 to detect the prolportion of iron added to the flour samples. It is found that only 45% of mills produced flour contain the prescribed percentage of iron (30-60 ppm) while 51.9% of the mills produced flour at rate is less or much more than the prescribed percentage, while only 4.1% of the mills were not added iron to the flour.

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Publication Date
Wed Aug 25 2021
Journal Name
2021 7th International Conference On Contemporary Information Technology And Mathematics (iccitm)
Anomaly Detection in Flight Data Using the Naïve Bayes Classifier
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
The Attitudees toward aggresive behaviore for sample of college of education and college of science for womens student: The Attitudees toward aggresive behaviore for sample of college of education and college of science for womens student
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Abstract
The purposes of this study were to identifying the (attitudes of college of
education and college of science for womens in Baghdad university students
toward aggresive behaviore) and to determine the differences of student's
attitudes due to Specialization.
The study sample consists of (460) Female students.Aquestionave of
(59) items was desiged and distributed selected sample after established it's
validity and reliablity.The results indicated that the attitude of Baghdad
University For College of education and college of science students toward
aggresive behaviore were Negative.
The findings revealed that there were statistically significant differences
in the student's attitudes due to special

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