Preferred Language
Articles
/
7hb2-okBVTCNdQwCe46x
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
...Show More Authors
Abstract<p>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.</p>
Scopus Clarivate Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Aug 08 2025
Journal Name
Jornal Of Al-muthanna For Agricultural Sciences
A Proposed Approach to Agricultural Extension in Iraq for a Better Response to the Needs of farmer’s to Address Their Challenges
...Show More Authors

View Publication
Publication Date
Thu Oct 18 2018
Journal Name
Al–bahith Al–a'alami
Public exposure to news satellite channels and its relationship to levels of preference and evaluation of programs: Survey study on a sample of the audience of Baghdad City Cente
...Show More Authors

The media, especially the satellite channels in our time, are one of the most important pillars of daily life, public and private, for society and people, and are considered by sociologists and sociologists as one of the most important factors of social upbringing and the most important, as a result of the technological and technological development of the media as well as increasing their numbers and vertical and horizontal expansion locally, As well as entering into the lives of individuals and people and leading them to important sites within their interests and preferences, not to mention the long time spent exposure to those media and benefit from the programs offered or broadcast. , The problem of this research is that there is a l

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Jun 01 2020
Journal Name
مجلة العلوم و التكنولوجية للنشاطات البدنية و الرياضية/ الجزائر
The effect of using the five-finger strategy on learning movement chain on a balance beam in the artistic gymnastics of women
...Show More Authors

Abstract: The aim of the research identify the effect of using the five-finger strategy in learning a movement chain on the balance beam apparatus for students in the third stage in the College of Physical Education and Sports Science, as well as to identify which groups (experimental and controlling) are better in learning the kinematic chain on the balance beam device, has been used The experimental approach is to design the experimental and control groups with pre-and post-test. The research sample was represented by third-graders, as the third division (j) was chosen by lot to represent the experimental group, and a division Third (i) to represent the control group, after which (10) students from each division were tested by lot to repr

... Show More
View Publication Preview PDF
Publication Date
Fri Mar 20 2020
Journal Name
Remote Sensing
Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics
...Show More Authors

The smart city concept has attracted high research attention in recent years within diverse application domains, such as crime suspect identification, border security, transportation, aerospace, and so on. Specific focus has been on increased automation using data driven approaches, while leveraging remote sensing and real-time streaming of heterogenous data from various resources, including unmanned aerial vehicles, surveillance cameras, and low-earth-orbit satellites. One of the core challenges in exploitation of such high temporal data streams, specifically videos, is the trade-off between the quality of video streaming and limited transmission bandwidth. An optimal compromise is needed between video quality and subsequently, rec

... Show More
View Publication
Scopus (2)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
...Show More Authors

The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

... Show More
View Publication Preview PDF
Scopus
Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use The Coiflets and Daubechies Wavelet Transform To Reduce Data Noise For a Simple Experiment
...Show More Authors

In this research, a simple experiment in the field of agriculture was studied, in terms of the effect of out-of-control noise as a result of several reasons, including the effect of environmental conditions on the observations of agricultural experiments, through the use of Discrete Wavelet transformation, specifically (The Coiflets transform of wavelength 1 to 2 and the Daubechies transform of wavelength 2 To 3) based on two levels of transform (J-4) and (J-5), and applying the hard threshold rules, soft and non-negative, and comparing the wavelet transformation methods using real data for an experiment with a size of 26 observations. The application was carried out through a program in the language of MATLAB. The researcher concluded that

... Show More
Publication Date
Sat Sep 01 2018
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
The Factors Affecting on Managing Sensitive Data in Cloud Computing
...Show More Authors

Cloud computing represents the most important shift in computing and information technology (IT). However, security and privacy remain the main obstacles to its widespread adoption. In this research we will review the security and privacy challenges that affect critical data in cloud computing and identify solutions that are used to address these challenges. Some questions that need answers are: (a) User access management, (b) Protect privacy of sensitive data, (c) Identity anonymity to protect the Identity of user and data file. To answer these questions, a systematic literature review was conducted and structured interview with several security experts working on cloud computing security to investigate the main objectives of propo

... Show More
View Publication
Scopus (5)
Crossref (1)
Scopus Crossref
Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Application of Data Mining Techniques on Tourist Expenses in Malaysia
...Show More Authors

Tourism plays an important role in Malaysia’s economic development as it can boost business opportunity in its surrounding economic. By apply data mining on tourism data for predicting the area of business opportunity is a good choice. Data mining is the process that takes data as input and produces outputs knowledge. Due to the population of travelling in Asia country has increased in these few years. Many entrepreneurs start their owns business but there are some problems such as wrongly invest in the business fields and bad services quality which affected their business income. The objective of this paper is to use data mining technology to meet the business needs and customer needs of tourism enterprises and find the most effective

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Opcion, Año
Active Learning And Creative Thinking
...Show More Authors

Active Learning And Creative Thinking

Publication Date
Fri Feb 04 2022
Journal Name
Neuroquantology
Detecting Damaged Buildings on Post-Hurricane Satellite Imagery based on Transfer Learning
...Show More Authors

In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

... Show More
View Publication
Scopus (3)
Scopus Crossref