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.
Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th
Water provision is sensitive to climate change, and agricultural production and food supply are sensitive to water availability. Water scarcity affects food security and agricultural economic development through changes in agricultural production and changes in the composition of produced goods. Recent droughts also led to a decrease in the volume of water allocated to agriculture, which led to a decrease in total agricultural production and exports, and this has subsequent impacts on food security and economic development. The research aimed to measure the impact of water scarcity on agricultural economic development for the period 1990-2022. The research included three behavioral equations with three endogenous variables: the cult
... Show MoreThis paper is an attempt to foster creative performance of students in essay writing through using tips. Prewriting tips are a series of strategies ( outline in essay writing). These tips enable :::e Iraqi students to be aware of the process of writing as a guideline to what is expected from them as good essay writers. The study aims at: I .Finding out whether college students are aware of using these tips in fostering creativity performance in their essay writing? 2. To what extent can the application of these tips contribute in developing students' essay writing? To achieve these aims. 2 questionnaire and a test have been conducted and distributed on two parallel th
... Show MoreDrought is a natural phenomenon in many arid, semi-arid, or wet regions. This showed that no region worldwide is excluded from the occurrence of drought. Extreme droughts were caused by global weather warming and climate change. Therefore, it is essential to review the studies conducted on drought to use the recommendations made by the researchers on drought. The drought was classified into meteorological, agricultural, hydrological, and economic-social. In addition, researchers described the severity of the drought by using various indices which required different input data. The indices used by various researchers were the Joint Deficit Index (JDI), Effective Drought Index (EDI), Streamflow Drought Index (SDI), Sta
... Show MoreOne of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
... Show MoreIn this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A
... Show MoreDeep Learning Techniques For Skull Stripping of Brain MR Images
Gender and culture are among the factors that influence the process of understanding and interpreting different types of communication, especially images. The current study, which is a part of a master’s thesis, aims at investigating the role of gender and culture in interpreting and understanding the caricatures that deal with women’s issues in Arab societies. To this end, the researchers adopted Barthes’ (1957) concepts of denotation and connotation in his theory of mythologies in addition to Langacker’s (1987) theory of (Domains). The research concludes that the female subjects have better cognitive abilities in investing the signs within the selected caricatures. The other factor the study reached to is that the respondents
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