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 scholars differed very much in determining the grammatical doctrine of Ibn Qaysan. It was said that he confused between the two sects and took the two groups(1) and that he took from Abu Abbas the fox and Abu al-Abbas almabrd(2).He was descended from the two sheikhs almbrad and fox(3), This research to find out his grammatical opinions in the tools and grammatical words that appeared in the Book of Resonance of Multiplication to the many reported by Ibn Hayyan in it, he has seen the books of Ibn Kisan did not reach us.
The collection of these opinions and analysis is important for the scholars. Because the books of Ibn Kaysan specialized in grammar have lost their most important, the books that are similar to the book of Ibn al-Ha
The objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
... Show MoreSchiff base ligand (H2CANPT) was prepared by two steps: first, by the condensation of curcumin with 4-amino antipyrin produces4,4'-(((1E,3Z,5Z,6E)-1,7-bis(4-hydroxy-3- methoxyphenyl)hepta-1,6-diene-3,5-diylidene)bis(azanylylidene))bis(1,5-dimethyl-2-phenyl- 1,2-dihydro-3H-pyrazol-3-one) (CANP). Second, by the condensation of (CANP) with L-tyrosine produces2,2'-(((3Z,3'Z)-(((1E,3Z,5Z,6E)-1,7-bis(4-hydroxy-3-methoxyphenyl)hepta 1,6-diene-3,5-diylidene)bis(azanylylidene))bis(1,5-dimethyl-2-phenyl-1,2-dihydro-3-H-pyrazole- 4-yl-3-ylidene))bis(azanylylidene))bis(3-(4-hydroxyphenyl)propanoic acid) (H2CANPT). The resulted Schiff comported as hexadentate coordinated with (N4O2) atoms, then it was treated with some transition and non-transaction met
... Show MoreDialysis is a stressful process and follows various psychological and social problems, which can lead to psychological disturbances. Patients on dialysis experience psychological distress, and the reduction of stress in patients provides psychological resources to cope with their physical condition. The study aimed to evaluate the effect of deep-breathing exercise training on the level of stress among maintenance hemodialysis patients.
This study is a randomized
At the local level in the early 1990s first established an Islamic bank 1993 is called Iraqi Islamic bank and was established by Dr. abdullatef hmim and with capital of 200 Million Iraqi dinars .
After 2003 began the attention of Iraqis tend to create Islamic banks until now up to 30 banks in the present , He confirmed Mr. Governor of the Iraqi Central Bank recently that there is more than 40 iintroduction licence to establish an Islamic bank in Iraq , That banking activity which is compatible with Sharia law widely welcomed by savers and those in need for more development and modernization in order to gain a greater share within the Iraqi market , and allowed the Iraqi Central Bank in recent years
... Show MoreAn essential element in English as a foreign language (EFL) learning is vocabulary. There is a big emphasis on learning the new words' meaning from the books or inside classrooms. Also, it is a major part of language teaching as well as being fundamental to the learner but there is a big challenge in vocabulary instruction due to the weak confidence by teachers in selecting the suitable practice in teaching vocabulary or they sometimes unable to specify a suitable time for it during the teaching process. The major aim of this study is to investigate the value of posters in vocabulary learning on the 2nd grade students at Halemat Alsaadia High School in Baghdad – Iraq. It hypothesized that there are no statistically significant differences
... Show MoreTo expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo
... Show MoreMicro metal forming has an application potential in different industrial fields. Flexible tool-assisted sheet metal forming at micro scale is among the forming techniques that have increasingly attracted wide attention of researchers. This forming process is a suitable technique for producing micro components because of its inexpensive process, high quality products and relatively high production rate. This study presents a novel micro deep drawing technique through using floating ring as an assistant die with flexible pad as a main die. The floating ring designed with specified geometry is located between the process workpiece and the rubber pad. The function of the floating ring in this work is to produce SS304 micro cups with profile
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.