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.
La disciplina sémantica siendo una rama de la lingüística y relacionada con los significados que residen detrás de los vocablos sería muy intereseante ser estudiada y investigada, sobre todo cuando tratamos de penetrarnos dentro de la evolución semántica y los motivos por los que se suceden estos cambios. Pues, es injusto dejar de dar una definición aclaratoria sobre esta disciplina y sus componentes.
El significado de los léxicos que se forma por un conjunto de semas o rasgos significativos mínimos. Sin embargo, no todos esos semas son igualmente intervenidos por los hablantes de una comunidad lingüística, sino que hay algunos de ellos que siempre están presentes, mientras que otros varían. Es decir, el significado
... Show MoreThe simulation have been made for 3D flow structure and heat transfer with and without
longitudinal riblet upstream of leading edge vane endwall junction of first stage nozzle guide vane .The research explores concept of weakening the secondary flows and reducing their harmful effects.Numerical investigation involved examination of the secondary flows ,velocity and heat transfer rates by solving the governing equations (continuity, Navier -stokes and energy equations ) using the known package FLUENT version (12.1).The governing equations were solved for three dimentional, turbulent flowe, incompressible with an appropriate turbulent model (k-ω,SST) .The numerical solution was carried out for 25 mode
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The current research aims to identify the effectiveness of concept maps in the academic achievement of the art of elegance and fashion for third vocational students. The current research is a quasi-experimental one. The research sample consisted of (74) female students in Al-Saydiyah secondary school for girls, they were divided into two groups: the experimental group and the control group. The following hypothesis was developed: There are no statistically significant differences at the level (0.05) between the average scores of the students who studied the subject using concept maps and the average scores of the students who studied the subject in the traditional method in the post-achievement test. The
... Show MoreThis research aims to study the optical characteristics of semiconductor quantum dots (QDs) composed of CdTe and CdTe/CdSe core-shell structures. It utilizes the refluxed method to synthesize these nanoscale particles and aims to comprehend the growth process by monitoring their optical properties over varied periods of time and pH 12. Specifically, the optical evolution of these QDs is evaluated using photoluminescence (PL) and ultraviolet (UV) spectroscopy. For CdTe QDs, a consistent absorbance and peak intensity increase were observed across the spectrum over time. Conversely, CdTe/CdSe QDs displayed distinctive absorbance and peak intensity variations. These disparities might stem from irregularities in forming selenium (Se) layers a
... Show MoreBackground: Thalassemias are a group of heterogeneous genetic disorders, in which the rate of production of hemoglobin is partially or completely suppressed due to reduced rate of synthesis of α or β- chain
Objectives: to estimate the prevalence of Hepatitis C infection among B thalassemia patients attending Ibn-AL-Baladi center of blood diseases in AL-Sader city, in AL-Resafa Quarter of Baghdad and to determine the possible risk factors.
Type of the study: Cross- sectional study.
Methods: A cross sectional study conducted on B Thalassemia patients attending the blood diseases center in Ibn-AL-Baladi hospital during the period from 1st
... Show MoreEstimation the unknown parameters of a two-dimensional sinusoidal signal model is an important and a difficult problem , The importance of this model in modeling Symmetric gray- scale texture image . In this paper, we propose employment Deferential Evaluation algorithm and the use of Sequential approach to estimate the unknown frequencies and amplitudes of the 2-D sinusoidal components when the signal is affected by noise. Numerical simulation are performed for different sample size, and various level of standard deviation to observe the performance of this method in estimate the parameters of 2-D sinusoidal signal model , This model was used for modeling the Symmetric gray scale texture image and estimating by using
... Show MoreObjective(s): To determine the impact of the Electronic Health Information Systems upon medical, medical backing and administrative business fields in Al-Kindy Teaching Hospital and to identify the relationship between such impact and their demographic characteristics of years of employment, place of work, and education. Methodology: A descriptive analytical design is employed through the period of April 25th 2016 to May 28th 2016. A purposive "non- probability" sample of (50) subject is selected. The sample is comprised of (25) medical and medical backing staff and (25) administrative staff who are all