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

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

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

This study objective is to identify the visual pollution in Karrada district main streets as an example of main streets in Baghdad, the public opinion about each pollutants, solutions to reduce and eliminate the pollution were suggested as well. In order to accomplish this objective different methods were used, 16 pollutants were selected, pictures of each pollutants were taken and a questioner were distributed randomly for 270 people to evaluate the public opinion with statistical methods. Garbage, their disposal and storage areas took the first two places as the highest offensive pollutants. The people showed that they find long lines of vehicles, debris and generators appearance ranked third, fourth and fifth respectively .This resear

This research includes a detailed morphological description of the Pollenia mesopotamica sp. nov. in Iraq. Locality, host plant and data of collection were given.

Industry represents a cornerstone of the process of economic development and a measure of progress and contribute to increased prosperity and high standard of living.

The researcher analyzed the productivity indicators in industrial facilities large and small at several time periods ranging from 1970 to 2009, according to the economic situation that prevailed in each period.

    Different impact of periods under discussion, it made ​​Iraq the cash surpluses during the period 70-1980 then the effects of the war after 1980 and the economic blockade since 1990, and the subsequent events of the year

This research attempts to shed light on a topic that is considered one of the most important topics of HRMs management, which is the Employee centric approach by examining its philosophy and understanding . To achieve the goal, the research relied on the philosophical analytical method, which is one of the approaches used in theoretical studies. The research reached a set of conclusions, the most important of which are the theoretical studies that addressed this entry in the English language and the lack of it in the Arabic language, according to the researcher's knowledge. The research reached a set of recommendations, the most important of which was that this approach needs more research, analysis and study at the practical and th

The In this experimental study, natural stone powder was utilized to improve a cohesive soil’s compaction and strength properties. According to the significant availability of limestone in the globe, it has been chosen for the purpose of the study, in addition to considering the existing rock industry massive waste. Stone powder was used in percentages of 4, 8, 12, 16% replaced from the soil weight in dry state. Some of cohesive soil’s consistency, shear, and compaction properties were depicted after improvement. The outcomes yielded in significant amendments in the experimented geotechnical properties after stone powder addition considering 60 days curing period. Cohesion and friction angle were notably increased by