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.
Vorwort:
Die Übersetzung gilt in der Vergangenheit als Brücke zwischen verschiedenen Gesellschaften. Sie spielt eine große Rolle im Bereich Kulturaustausch der Länder. Die Araber haben das früh betrachtet, und die Übersetzung als Wissenschaft wird eine der wichtigsten Lehren. Viele griechische Wissenschaften waren durch Übersetzung in den arabischen Ländern bekannt.
In dieser Forschung findet man einen Überblick über die Wichtigkeit der Sprichwörterübersetzung und welche Rolle spielt diese Übersetzung im Z
... Show MoreThe angiotensin converting enzyme (ACE) I\D gene polymorphism influences the blood ACE enzyme activity. Renoprotective effect of ACE inhibitors (ACEIs) varies among patients due to genetic variation, particularly in Renin-Angiotensin-Aldosterone System genes. This study investigates the genetic variations of ACE I\D and AGT1RA1166C gene polymorphisms in the antiproteinuric effect of ACEI therapy in type 2 diabetes mellitus (T2DM) patients. This is a cross-sectional study that included 76 T2DM patients who are ACEI users, divided into two groups: T2DM without diabetic kidney disease (DKD) included 31 patients, and T2DM with DKD included 45 patients. Urine samples were taken for measurement of urine albumin and creatinine, then calcul
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The current research relied on the descriptive approach, in analyzing his sample, which was deliberately chosen, Among the most imp
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... Show MoreAbstract:
The aim of the present research is to evaluate the child’s nutritional
method (2-5 years old) which is based on his resistance of the food highly rich
with nutritional elements and his acceptance of the food of a low nutritional
value in addition to his having forbidden food with other mates and making
use of all mates when having food, in establishing the sound social values and
affection since child hood. The required statistical equation have been used
by the researcher namely (Z test).
The sample of the present study consists of (26) children who were selected
intentionally and randomly from the kindergartens of Al-Bayaa region and the
college of Education for women. The questionnaires were d