Image Fusion is being used to gather important data from such an input image array and to place it in a single output picture to make it much more meaningful & usable than either of the input images. Image fusion boosts the quality and application of data. The accuracy of the image that has fused depending on the application. It is widely used in smart robotics, audio camera fusion, photonics, system control and output, construction and inspection of electronic circuits, complex computer, software diagnostics, also smart line assembling robots. In this paper provides a literature review of different image fusion techniques in the spatial domain and frequency domain, such as averaging, min-max, block substitution, Intensity-Hue-Saturation(IHS), Principal Component Analysis (PCA), pyramid-based techniques, and transforming. Different quality metrics for quantitative analysis of these approaches have been debated.
HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
The goal of the research is to theoretically establish the variable of brilliant leadership and explain the importance of this variable and the philosophical orientation of researchers in taking it as an original variable in their research as an independent variable. The descriptive approach and theoretical framing of brilliant leadership were followed. We relied on secondary data represented by books, dissertations, dissertations, scientific research, and the information network (the Internet) as a tool for collecting data. The scientific value was represented by the importance of consolidating brilliant leadership and reviewing the most important things that were confirmed by the research and studies that dealt with this research.
... Show MoreDeep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreBackground: Inflammation of the brain parenchyma brought on by a virus is known as viral encephalitis. It coexists frequently with viral meningitis and is the most prevalent kind of encephalitis. Objectives: To throw light on viral encephalitis, its types, epidemiology, symptoms and complications. Results: Although it can affect people of all ages, viral infections are the most prevalent cause of viral encephalitis, which is typically seen in young children and old people. Arboviruses, rhabdoviruses, enteroviruses, herpesviruses, retroviruses, orthomyxoviruses, orthopneumoviruses, and coronaviruses are just a few of the viruses that have been known to cause encephalitis. Conclusion: As new viruses emerge, diagnostic techniques advan
... Show MoreThe purpose of this article is to provide a comprehensive definition of corporate governance and to review the existing literature on the subject. The researchers examine various corporate governance theories, including agency theory, stakeholder theory, and resource-based theory. The study concludes by emphasizing that the primary goal of corporate governance theories is not to examine how managers govern but rather to analyze how governance operates in an company.
Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec
... Show MoreBackground:sThe aims of this study were to evaluate and compare the ability of three different techniques to obdurate simulated lateral canals, evaluate the effect of the main canal curvature on obturation of lateral canals and compare the gutta-percha penetration between coronal and apical lateral canals. Materials and methods: Resin blocks with 30 straight and 30 curved were used in this study. Each canal has two parallel lateral canals. The main canal has 0.3 mm apical diameter and 0.04 taper. The canals were divided into six groups according to canal curvature and obturation techniques used (n=10): Groups C1 and C2: straight and curved canals obturated with continuous wave technique using E&Q masterTM system. Groups O1 and O2: straight
... Show MoreObjectives. This study was carried out to quantitatively evaluate and compare the sealing ability of Endoflas by using differentobturation techniques. Materials and Methods. After 42 extracted primary maxillary incisors and canines were decoronated, theircanals were instrumented with K files of size ranging from #15 to #50. In accordance with the obturation technique, the sampleswere divided into three experimental groups, namely, group I: endodontic pressure syringe, group II: modified disposable syringe,and group III: reamer technique, and two control groups. Dye extraction method was used for leakage evaluation. Data wereanalyzed using one-way ANOVA and Dunnett’s T3 post hoc tests. The level of significance was set at p<0:05. Results.
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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