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.
Pharmaceutical-instigated pollution is a major concern, especially in relation to aquatic environments and drugs such as meropenem antibiotics. Adsorbents, such as multi-walled carbon nanotubes, offer potential as means of removing polluting meropenem antibiotics and other similar compounds from water. In order to evaluate the effectiveness of multi-walled carbon nanotubes in this capacity, various experimental parameters, including contact time, initial concentration, pH, temperature and the dose of adsorbent have been investigated. The Langmuir and the Freundlich isotherm models have been used. The data obtained using a modified Langmuir model have been consistent with the experimental ones; the best pH value has been obtained to have the
... Show MoreIt is out of question that USA foreign policy has a great superiority and
influence all over the world.
This study deals with all dimensions; aims; and challenges of the American
foreign policy. It aims to answer the following question: within the current changes in
the world, how can the aims of the American foreign policy be realized?
Givers of foreign Audit about Social Responsibility of Profit Organization. The recent time is charcterstically with big economic Organization activities, because there are many transactions between these Organizations and different financial markets development techniques.
This encourgage business men to increase their efforts for investment in these markets. Because the Accounting is in general terms it represents a language of these Unions Activities and translate them in to fact numbers, for that there is need for Accounting recording for certain of these Organizations behavior and their harmonization with their Objectives.
In this respect the Audit function comes to che
... Show MoreRemoval of heavy metals from waste water has received a great deal of attention. The compare Cr
(VI) adsorption characteristics removing from wastewater by using thermally modified and non-modified
eggshells were examined
The study examines the root causes of delays that the project manager is unable to resolve or how the decision-maker can identify the best opportunities to get over these obstacles by considering the project constraints defined as the project triangle (cost, time, and quality) in post-disaster reconstruction projects to review the real challenges to overcome these obstacles. The methodology relied on the exploratory description and qualitative data examined. 43 valid questionnaires were distributed to qualified experienced engineers. A list of 49 factors causes was collected from previous international and local studies. A Relative Important Index (RII) is adapted to determine the level of importance of each sub-criterion in the fou
... Show MoreThe successive international changes in the economic, political, cultural and other fields resulted in many phenomena that occupied different levels of interest, and have been followed up, studied and analysed by specialists and researchers especially under the development of the media in the global communication.
Even though these phenomena had reflections in the communication domain like development and changes in the mechanism of behaviours between the international communities, they created in the meantime a phenomenon that caused an imbalance in the production, spread and the use of the informations that were supposed to be for fewer than 5 countries whereas it actually it is for more than 180 countries.