General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

Professional learning societies (PLS) are a systematic method for improving teaching and learning performance through designing and building professional learning societies. This leads to overcoming a culture of isolation and fragmenting the work of educational supervisors. Many studies show that constructing and developing strong professional learning societies - focused on improving education, curriculum and evaluation will lead to increased cooperation and participation of educational supervisors and teachers, as well as increases the application of effective educational practices in the classroom.

The roles of the educational supervisor to ensure the best and optimal implementation and activation of professional learning soci

                  The current study aims to apply the methods of evaluating investment decisions to extract the highest value and reduce the economic and environmental costs of the health sector according to the strategy.In order to achieve the objectives of the study, the researcher relied on the deductive approach in the theoretical aspect by collecting sources and previous studies. He also used the applied practical approach, relying on the data and reports of Amir almuminin Hospital for the period (2017-2031) for the purpose of evaluating investment decisions in the hospital. A set of conclusions, the most important of which is: The failure to apply

Decision-making in Operations Research is the main point in various studies in our real-life applications. However, these different studies focus on this topic. One drawback some of their studies are restricted and have not addressed the nature of values in terms of imprecise data (ID). This paper thus deals with two contributions. First, decreasing the total costs by classifying subsets of costs. Second, improving the optimality solution by the Hungarian assignment approach. This newly proposed method is called fuzzy sub-Triangular form (FS-TF) under ID. The results obtained are exquisite as compared with previous methods including, robust ranking technique, arithmetic operations, magnitude ranking method and centroid ranking method. This

هدف البحث إلى التعرف على مستوى الثقافة الغذائية الرياضية لدى عدائي مسافات ركض (400 و800) و(400) متر حواجز الشباب، والتعرف على العلاقة وإسهام وأثر الثقافة الغذائية الرياضية ببعض المؤشرات البيوكيميائية لدى عدائي مسافات ركض (400 و800) و(400) متر حواجز الشباب، أعتمد المنهج الوصفي بأسلوب العلاقات الإرتباطية، و تمثلت حدود مجتمع البحث بالعدائين الشباب لفعاليات ركض (400 و800) و(400) متر حواجز، يمثلون لاعبي الأندية العراقية الب

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

Witnessing the global arena many changes in the political, economic, social, scientific and technological have left their mark on the world as a whole, these changes require necessarily Advancement of the profession of auditing, and improve their performance, especially after the mixer skepticism the health of approach and the method followed by a check in the major audit firms global view as for the external audit of an active role in providing services to members of the community in various sectors, were to be provide these services to the highest level of quality.To ensure the quality of the audit process to be a proper planning is based on a scientific basis to be the substrate a strong underlying different audit works, and if planni