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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
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Comparison of Practical Investigations for CO Emissions Emitted From Single Cylinder S. I. Engine Fueled With Different Kinds of Hydrocarbon Fuels and Hydrogen
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Liquefied petroleum gas (LPG), Natural gas (NG) and hydrogen were all used to operate spark ignition internal combustion engine Ricardo E6. A comparison of CO emissions emitted from each case, with emissions emitted from engine fueled with gasoline as a fuel is conducted.

The study was accomplished when engine operated at HUCR for gasoline n(8:1), was compared with its operation at HUCR for each fuel. Compression ratio, equivalence ratio and spark timing were studied at constant speed 1500 rpm.

CO concentrations were little at lean ratios; it appeared to be effected a little with equivalence ratio in this side, at rich side its values became higher, and it appeared to be effected by equivalence ratio highly, the results s

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Publication Date
Wed Apr 01 2026
Journal Name
Journal Of Dentistry
Comparison of the accuracy of Robotic arm and Dynamic Navigation in the placement of mandibular dental implants: An in-vitro study
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Publication Date
Thu Jul 23 2026
Journal Name
Journal Of Baghdad College Of Dentistry
The effect of curvature angle and rotational speed on the cyclic fatigue of three types of rotary instrument (In vitro): comparative study
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Background: The fracture of instruments within root canal during endodontic treatment is a common incidence, fracture because of fatigue through flexure occurs due to metal fatigue, this study aimed to assess the effect of curvature angle and rotational speed on the cyclic fatigue of different type of Endodontic NiTi Rotary Instruments and compare among them. Materials and method: Three types of rotary instruments with tip size 0.25: ProTaPer F2 (Densply, Malifier) Revo-S SU( 0.06 taper, MicroMega) and RaCe system (0.06 taper, FKG, Dentaire), Forty file of each instrument were used within two canals with angle of curvature (40 &60 )at two speed (250&400)RPM, twelve group were formed for all instruments(total number=120),ten file fo

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Publication Date
Wed Jul 19 2017
Journal Name
International Journal Of Advances In Chemical Engineering And Biological Sciences
Detection of Aflatoxin M1 in Pasteurized Canned Milk and Using of UV Radiation for Detoxification
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The current study was designed to investigate the presence of aflatoxin M1 in 25 samples of pasteurized canned milk which collected randomly from some Iraqi local markets using ELISA technique. Aflatoxin M1 was present in 21 samples, the concentration of aflatoxin M1 ranged from (0.25-50 ppb). UV radiation (365nm wave length) was used for detoxification of aflatoxin M1 (sample with highest concentration /50 ppb of aflatoxin M1 in two different volumes ((25 & 50 ml)) for two different time (15 & 30 min) and 30, 60, 90 cm distance between lamp and milk layer were used for this purpose). Results showed that distance between lamp and milk layer was the most effective parameter in reduction of aflatoxin M1, and whenever the distance increase the

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Publication Date
Wed Dec 13 2023
Journal Name
2023 3rd International Conference On Intelligent Cybernetics Technology & Applications (icicyta)
GPT-4 versus Bard and Bing: LLMs for Fake Image Detection
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The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Hurst Exponent and Tsallis Entropy Markers for Epileptic Detection from Children
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The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
The Influence of NMI against Modularity in Community Detection Problem: A Case Study for Unsigned and Signed Networks
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Community detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo

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Publication Date
Sun Mar 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Single Face Detection on Skin Color and Edge Detection
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Publication Date
Tue Sep 23 2025
Journal Name
Sensing And Imaging
A Review of Detection, Monitoring, and Analysis Techniques in Terahertz Sensing for Sustainable Agriculture
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Terahertz (THz) technology, which uses radiation lying between microwave and infrared in the electromagnetic spectrum, could revolutionize digital agriculture through terahertz’s ability to assess agricultural materials accurately and non-destructively. The review discusses notable developments in THz applications to digital agriculture: real-time crop monitoring, nutrient and disease detection, soil moisture and contaminant analysis, and supply chain traceability. The developments have emerged from studies in time-domain spectroscopy, imaging, machine learning (ML), and blockchain integration. Despite the promising advances in THz agricultural applications, limitations remain, such as limited penetration depth, high system costs, and ope

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Publication Date
Sat Mar 28 2026
Journal Name
Journal Of Physical Education
The relationship between decision-making time and accuracy of jump shooting among students at the college of physical education and Sports Sciences in handball
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The study aimed to analyze the nature of the relationship between decision-making time and the accuracy of shooting by jumping among handball players who are students of the fourth stage at the College of Physical Education and Sport Sciences to reveal the extent to which cognitive-motor ability contributes to improving offensive skill performance. The study adopted a descriptive approach using the method of relational relationships, and 20 players who were selected deliberately participated. The study used a reaction time system to measure decision time, as well as test the accuracy of shooting from jumping from three specific points within the attack area. The results showed that the Arithmetic mean decision time was 0.828 seconds

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