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.
Abstract:
We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.
In this research, I estimate the reliability function of cluster function by using the seemingly unrelate
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
... Show MoreTraumatic spinal cord injury is a serious neurological disorder. Patients experience a plethora of symptoms that can be attributed to the nerve fiber tracts that are compromised. This includes limb weakness, sensory impairment, and truncal instability, as well as a variety of autonomic abnormalities. This article will discuss how machine learning classification can be used to characterize the initial impairment and subsequent recovery of electromyography signals in an non-human primate model of traumatic spinal cord injury. The ultimate objective is to identify potential treatments for traumatic spinal cord injury. This work focuses specifically on finding a suitable classifier that differentiates between two distinct experimental
... Show MoreThe research aims to measure the efficiency of health services Quality in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency for two types of orientation direction, which are input and output oriented direction.
The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).
The accurate extracting, studying, and analyzing of drainage basin morphometric aspects is important for the accurate determination of environmental factors that formed them, such as climate, tectonic activity, region lithology, and land covering vegetation.
This work was divided into three stages; the 1st stage was delineation of the Al-Abiadh basin borders using a new approach that depends on three-dimensional modeling of the studied region and a drainage network pattern extraction using (Shuttle Radar Topographic Mission) data, the 2nd was the classification of the Al-Abiadh basin streams according to their shape and widenings, and the 3rd was ex
... Show MoreBackground: Propolis has received great interest because of its wide range antimicrobial activity. Propolis also called (bee glue) due to its collection by (Apismellifera) honeybees from various plants resinous substance. The aim of this study was to determine the antibacterial effect of propolis extracts (aqueous and alcoholic) on anaerobic periodontal pathogen namely Aggregatibacteractinomycetemcomitans. Materials and Methods: Strains of Aggregatibacter actinomycetemcomitans wasisolated from pockets of systemically healthy patients aged between 35-55 years old suffering from chronic periodontitis with pocket depths of 5-6 mm, the bacteria cultured on special blood Agar plates solid media. Propolis was extracted by using water and alcohol.
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Objectives: The present study designed to explore the genotoxicity through measurement of Mitotic index in bone marrow and the spleen cells, as possible mechanism of bone marrow and spleen toxicity that induced by irinotecan; and to describe the protective actions of omega 3 against irinotecan induced genotoxicity in bone marrow and the spleen of rats.
Methods: Twenty four (24) rats (Sprague-Dawley) were randomly divided into four groups: Group Ӏ, rats received single oral daily dose of distilled water (2 ml/kg) for 25 days (negative control group); Group ӀӀ (irinotecan-treated), receiv
... Show MoreAs the banking sector is a strong influence on the country's economic growth,The solid financial well-being of anybank does not mean only a guarantee for its investors, It is also important for both owners and workers and for theeconomy in all its joints.The elements of capital adequacy and quality of assets are important to the functioning of thebanking business.In this study, the research sample included four private banks. Quarterly data were used for the period(2011 - 2018).Moreover, data is also collected from articles, papers, the World Wide Web (the Internet) and specializedinternational journals.In this research, an effort was made to try to find out the effect of (the ratio of the capital owned todeposits on the value of the bank),
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