Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

Emotion could be expressed through unimodal social behaviour’s or bimodal or it could be expressed through multimodal. This survey describes the background of facial emotion recognition and surveys the emotion recognition using visual modality. Some publicly available datasets are covered for performance evaluation. A summary of some of the research efforts to classify emotion using visual modality for the last five years from 2013 to 2018 is given in a tabular form.

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

      تبنت العديد من المؤسسات الأكاديمية التعلم الإلكتروني منذ سنوات ، وقد أثبت فاعليته في كثير من هذه المؤسسات لاسيما تلك المهتمة بتعلم اللغات الاجنبية. الا انه  مع انتشار جائحة كورونا اصبح التعليم الالكتروني  ضرورة ملحة في الجامعات في جميع أنحاء العالم ، بما في ذلك الجامعات العراقية.  تهدف الدراسة الحالية إلى تقصي أثر هذا الوباء على التعلم الإلكتروني في أحدى الكليات العراقية . يفترض الباحث أن تقبل ال

يتمتع العراق بموارد بشرية هائلة حيث يعد من البلدان الفتية، إلا أنه يعاني من أزمة رأس مال بشري تغذيها أزمة التعليم، ولكون التعليم أبرز مكونات رأس المال البشري فقد ذلك بشكل كبير على مؤشر رأس المال البشري في العراق، من هذا المنطلق وللدور الكبير الذي يلعبه الانفاق العام في أي مجال، جاءت هذه الدراسة للبحث في موضوع "الانفاق العام على التعليم ودوره في تحسين مؤشرات راس المال البشري التعليمية في العراق"، حيث هدف ه

Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.

Deep 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

After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

يَهدف البحث الحالي الى تعرف نمطي الشخصية (أ.ب) وكذلك اسلوبي التفكير (اللفظي – التصوري) لدى طلبة كلية الفنون الجميلة – قسم التربية الفنية .

ومن اجل تحقيق اهداف البحث والتعرف على نمطي الشخصية (أ.ب) فقد اختار الباحث (مقياس كلازر ، 1978) الذي تم استعماله في دراسة ( العاني ، 2013) والذي يتمتع بصدق وثبات جيدين ، ومقياس اسلوبي التفكير (اللفظي والتصوري) لـ(الطائي ،2018) المبني وفق نظرية التشفير الثنائي لمنظرها ( بايفيو – PIAV