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.
A filed experiment was carried out at one of the private farms at Al-Suwaira District, Wasit Governorate during the spring season 2021, in order to evaluate the effect of adding Fulyzme plus (biofertilizer) and the foliar application of green tea extract (organic nutrient) on growth and yield of pepper plant cv. California wonder. A factorial experiment (43) was carried out using RCBD Design with three replicates. The Fulyzme plus treatment was applied with four concentrations (0, 10, 20. and 30 g. L-1). The foliar application of green tea extract was applied with three concentrations which were 0, 2 and 4 ml. L-1. Results revealed significant effects of Fulyzme plus at 30 g. L-1 and the foliar application of green tea extract at
... Show MoreIn this study, we focused on the random coefficient estimation of the general regression and Swamy models of panel data. By using this type of data, the data give a better chance of obtaining a better method and better indicators. Entropy's methods have been used to estimate random coefficients for the general regression and Swamy of the panel data which were presented in two ways: the first represents the maximum dual Entropy and the second is general maximum Entropy in which a comparison between them have been done by using simulation to choose the optimal methods.
The results have been compared by using mean squares error and mean absolute percentage error to different cases in term of correlation valu
... Show MoreThe Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,
... Show MoreThe regression analysis process is used to study and predicate the surface response by using the design of experiment (DOE) as well as roughness calculation through developing a mathematical model. In this study; response surface methodology and the particular solution technique are used. Design of experiment used a series of the structured statistical analytic approach to investigate the relationship between some parameters and their responses. Surface roughness is one of the important parameters which play an important role. Also, its found that the cutting speed can result in small effects on surface roughness. This work is focusing on all considerations to make interaction between the parameters (position of influenc
... Show MoreThe stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery
... Show MoreA nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.
This study aims at suggesting flow as a strategy for training female EFL student-teachers in the teaching training course and finding out the effect of this strategy on their performance and their flow state. The training course syllabuses will be constructed according to the flow nine factors and the teaching skills. The measurement tools are the student-teacher performance checklist that has already been used by the department of English language and SHORT Flow State Scale (S FSS-2). The study population is represented with the (60) female student-teachers/ fourth stage/ evening studies at theEnglish department /college of education for women/the University of Baghdad. The study is used the experimental design in that (30) of the student-
... Show MoreThe problem of divorce from the phenomena that characterized the nature of privacy,
although their impact beyond the individual to include the community as a whole, the parties
to the relationship affected by divorce caused them harm moral and material for a long time,
resulting imbalance in the personal relationship and family and social relations because of the
high divorce rates, particularly in Iraq high rates of 28690 thousand cases in 2004 to 59 515
thousand cases in 2011 and an increase of more than (100%) during the period above, and this
rise caused by aggravation of many of the problems led the reasons for social, economic and
incompatibility spouses, health and lack of reproduction, not spending The wife a