Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for many applications dismissing the use of DL. Having sufficient data is the first step toward any successful and trustworthy DL application. This paper presents a holistic survey on state-of-the-art techniques to deal with training DL models to overcome three challenges including small, imbalanced datasets, and lack of generalization. This survey starts by listing the learning techniques. Next, the types of DL architectures are introduced. After that, state-of-the-art solutions to address the issue of lack of training data are listed, such as Transfer Learning (TL), Self-Supervised Learning (SSL), Generative Adversarial Networks (GANs), Model Architecture (MA), Physics-Informed Neural Network (PINN), and Deep Synthetic Minority Oversampling Technique (DeepSMOTE). Then, these solutions were followed by some related tips about data acquisition needed prior to training purposes, as well as recommendations for ensuring the trustworthiness of the training dataset. The survey ends with a list of applications that suffer from data scarcity, several alternatives are proposed in order to generate more data in each application including Electromagnetic Imaging (EMI), Civil Structural Health Monitoring, Medical imaging, Meteorology, Wireless Communications, Fluid Mechanics, Microelectromechanical system, and Cybersecurity. To the best of the authors’ knowledge, this is the first review that offers a comprehensive overview on strategies to tackle data scarcity in DL.
The federal state is usually based on a number of regions because it is based on the multiplicity of political entities. The federal experiments were based on the existence of two or more regions and each federal system has its own peculiarities. Administrative authority between the federal government and local elected bodies of local people of absolute relative independence does not threaten the entity of the state according to the Constitution and the law and on a regional or reformer basis and exercise its powers within the legal scope prescribed The relationship between the federal authority and the Kurdistan region is the first level of the relationship on the real level, especially since no other region in Iraq has been formed exce
... Show MoreAim of the Study: The paper aims at identifying the extent of the role of strategic leadership represented by its four dimensions (administrative, transformational, political, moral) in fulfilling the requirements of university governance (Context, message and Goal, Management orientation, Independence, Issue, Sharing)
Methodology: A survey is applied to (107) members of the teaching staff at the college of Administration and Economics/ University of Mosul. To achieve the goals of the study, the researcher makes use of a number of tools such as: questionnaire, statistical tools and methods (repetitions, perce
... Show MoreIn this paper, we study the growth of solutions of the second order linear complex differential equations insuring that any nontrivial solutions are of infinite order. It is assumed that the coefficients satisfy the extremal condition for Yang’s inequality and the extremal condition for Denjoy’s conjecture. The other condition is that one of the coefficients itself is a solution of the differential equation .
Tourist business organizations face a challenging and the risks dynamic environment reflected its impact on the community and generate extra under pressure in the responsibilities and burdens of exceptional and affected much of factors, accidents and risks as a result of the actions and attitudes of disasters variety may exceed the geography of States border, which requires the absorption of risks facing the tourism and how to manage and deal with them scientific and reasonable grounds for the diagnosis and treatment of risk and how to reduce the aggravation and the different kinds.
As risks affecting the most important and vital to organizations as a tourist aspects of the market share and styles tourist
... Show Moreاستهدف البحث تشخيص وتحليل الاسباب التي تجعل المرأة العراقية أكثر تأثراً من الرجل بعوامل التغيرات المناخية، فضلاً عن زيادة الوعي بقضية المرأة في هذا المجال، لأن موضوع دمجها في صياغة السياسات والاستراتيجيات المتعلقة بالتغير المناخي أصبح قضية عالمية، ويحتل مرتبة متقدمة في مؤشرات تحقيق أهداف التنمية المستدامة، وأستخدمت الباحثة المنهج الوصفي والتحليلي والاحصائي في تحليل محاور البحث، وتوصل البحث الى إستن
... Show Morewith an organized propaganda campaign. This military campaign was helped to formulate its speech by many institutions, research centers, and knowledge and intelligence circles in order to mobilize public opinion gain supporters and face the opponents by different means depending on a variety of styles to achieve its required effects.
After the US occupation of Iraq, US media fighters sought to influence the Iraqi public opinion and making them convinced them of the important presence of US military forces in Iraq which necessitated finding its justification through the use of persuasive techniques in its intensive propaganda campaigns.
This research discusses the most important
synthesis, Composition, Spectral, Geometry and Antibacterial Applications ofMn(||),Ni(||),Co(||),Cu(||) and Hg(||) schiff Base complexes of N2O2 mixed donor with 1,10-phenanthroline
The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.