Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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

Background: Few updated retrospective histopathological-based studies in Iraq evaluate a comprehensive spectrum of oro-maxillofacial lesions. Also, there was a need for a systematic way of categorizing the diseases and reporting results in codes according to the WHO classification that helps occupational health professionals in the clinical-epidemiological approach.

Objectives: to establish an electronic archiving database according to the ICD-10 that encompasses oro-maxillofacial lesions in Sulaimani city for the last 12 years, then to study the prevalence trend and correlation with clinicopathological parameters.

Subjects and Methods:  A descri

In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

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

Facing the receiver (critic) problematic understanding of modern art done, which turned positive professional image to symbolic language, which gave it authenticity previous Arts advantage, and this latest progress in critical reading contemporary and several mechanisms for analyzing literary texts and plastic, including textural fabric. And we suffer from the absence of cash the recipient culture (learner), so the current search goal focused on detecting structural mechanisms formative (Goldman) reading done modern art and its role in raising criticism knowledge (learner). Defining the theoretical framework of chapter II by discussing it; the first episode dealt with the textural fabric, while the latter was accomplished Studio talk, an

Abstract:
       This study is studied one method of estimation and testing parameters mediating variables in a structural equations model SEM is causal steps method, in order to identify and know the variables that have indirect effects by estimating and testing mediation variables parameters by the above way and then applied to Iraq Women Integrated Social and Health Survey (I-WISH) for year 2011 from the Ministry of planning - Central statistical organization to identify if the  variables having the effect of mediation in the model by the step causal methods by using AMOS program V.23, it was the independent variable X represents a phenomenon studied (cultural case of the

במחקר הזה ניתחנו מספר נאומים של שמעון פרס, אנחנו התמקדנו בהשפעה והשכנוע אצל שמעון פרס ואיך הוא יכול להעביר את המסרים של נאומיו בסגנון פרגמטי כדי להגיע ללבו של הציבור.

 גם כן, התמקדנו בסגנון הפוליטי שהוא חושב כי התחום הזה צריך להיות ברור מול הציבור וגם כן מול דעת הקהל הבינלאומי מתוך השימוש במונחים בעלי השפעה ושכנוע להגיע למטרות המבוקשות.

 במלים אחרות, שמעון פרס, לעתים, מתמקד בשפה מליצית ויעמוד הרב