Content-based image retrieval has been keenly developed in numerous fields. This provides more active management and retrieval of images than the keyword-based method. So the content based image retrieval becomes one of the liveliest researches in the past few years. In a given set of objects, the retrieval of information suggests solutions to search for those in response to a particular description. The set of objects which can be considered are documents, images, videos, or sounds. This paper proposes a method to retrieve a multi-view face from a large face database according to color and texture attributes. Some of the features used for retrieval are color attributes such as the mean, the variance, and the color image's bitmap. In addition, the energy, and the entropy which based on the gray level values in an image is too considered as the features. In addition to statistical approaches, models of artificial intelligence produce a desirable methodology that enhances performance in information retrieval systems, and the genetic algorithm depicts one of them. The GA is preferred for its power and because it can be used without any specific information of the domain. The experimental results conclude that using GA gives a good performance and it decreases the average search time to (60.15 milliseconds) compared with (722.25milliseconds) for traditional search.
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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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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The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co
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Background: Squamous cell carcinoma is a disease of elderly peopleand it is uncommon in people with less than 40 years old; however many literatures revealed that tumor developing in patients younger than forty years appears more aggressive at the time of diagnosis. The purpose of the present study was to focus on the clincopathological features of the oral SCC in different age groups. Material and methods: In this study thirty five cases of paraffin embedded tissue blocks of oral squamous cell carcinoma were studied. The age range was from 16 to 80 years. The clinicopathological data were recorded for evaluating the tumor characters according to age of patients. Results : The age was not significantly correlated to the clinicopathological
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The Research aims to investigate into reality in terms of planning and scheduling management process for sake the implementation and maintenance of irrigation and drainage projects in the Republic of Iraq, with an indication of the most important obstacles that impede the planning and scheduling management process for these projects and ways of addressing them and minimizing their effects. For the purpose of achieving the goal of the research, a sci
... Show MorePorosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol
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The aim of the research was to investigate the use of non-parametric tests in the analysis of the questionnaire and how to choose the appropriate test for testing the hypothesis of the study of crime motives in Khartoum State. The data were collected through the primary sources by designing a questionnaire and distributed to a sample of inmates in Khartoum state; the data were analysis by SPSS program using the analytical statistical method through using some of the suitable non-parametric tests for each case. The most important results of the research were: there was significant relationship between the type of crime and the age group therefore, we found that the age group (20-29) was the most frequent crime particularly, the fi
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Abstract Objective: The underlying molecular basis of ischemic heart diseases (IHDs) has not yet been studied among Iraqi people. This study determined the frequency and types of some cardiovascular genetic risk factors among Iraqi patients with IHDs. Methods: This is a cross-sectional study recruiting 56 patients with acute IHD during a 2-month period excluding patients >50 years and patients with documented hyperlipidemia. Their ages ranged between 18 and 50 years; males were 54 and females were only 2. Peripheral blood samples were aspirated from all patients for troponin I and DNA testing. Molecular analysis to detect 12 common cardiovascular genetic risk factors using CVD StripAssay® (ViennaLab Diagnostics GmbH, Austria) was performed
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