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.
The idea of a common defect of the guarantee has gone through many developments in terms of defining the concept of this defect, starting with civil legislation and passing through the United Nations convention on contracts for the international sale of goods of 1980 (the Vienna agreement) and ending with legislation on consumer protection, and the French judiciary had an important role in developing this idea, so this came. Research to study these developments while clarifying the Iraq law's position on them and explaining the extent to which Iraqi legislation has reached in taking these developments, as the concept of defect no longer includes the shortage in the price of the sale or what is missed by a valid purpose, but rather expand
... Show MoreThe present study aims at analyzing the polysemy of the English preposition in from the cognitive linguistic (CL) point of view using Evans' and Tyler's approach (2003). The perplexity faced by Iraqi second language learners (L2) due to the multi-usages of this preposition has motivated the researcher to conduct this study. Seventy-six second year university students participated in this experimental study. The data of the pre-test and post-test were analyzed by SPSS statistical editor. The results have shown the following: First, a progress of more than (0.05≤) has been detected as far as students' understanding of the multiple usages of the preposition in is concerned. Second, the results of the questionnaire have s
... Show Moreالنظام السياسي اليمني : دراسة في المتغيرات الداخلية
In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant
... Show MoreTransport is a problem and one of the most important mathematical methods that help in making the right decision for the transfer of goods from sources of supply to demand centers and the lowest possible costs, In this research, the mathematical model of the three-dimensional transport problem in which the transport of goods is not homogeneous was constructed. The simplex programming method was used to solve the problem of transporting the three food products (rice, oil, paste) from warehouses to the student areas in Baghdad, This model proved its efficiency in reducing the total transport costs of the three products. After the model was solved in (Winqsb) program, the results showed that the total cost of transportation is (269,
... Show MoreFractal image compression depends on representing an image using affine transformations. The main concern for researches in the discipline of fractal image compression (FIC) algorithm is to decrease encoding time needed to compress image data. The basic technique is that each portion of the image is similar to other portions of the same image. In this process, there are many models that were developed. The presence of fractals was initially noticed and handled using Iterated Function System (IFS); that is used for encoding images. In this paper, a review of fractal image compression is discussed with its variants along with other techniques. A summarized review of contributions is achieved to determine the fulfillment of fractal image co
... Show MoreBackground: Malnutrition is an adverse prognostic factor in the outcome of children with standard risk acute lymphoblastic leukemia due to a significantly higher rate of bone marrow relapse in the malnourished patients. The event free survival of children with acute lymphoblastic leukemia in developed countries has increased substantially in the last two decades as treatment with intensive protocols has brought the estimated probability of event free survival at 5 years close to 75%. Although the prognosis of acute lymphoblastic leukemia has also been improved in underdeveloped countries, the figures for event free survival are lower, even when aggressive protocols are used. Unfavorable socioeconomic fa
... Show MoreThe Iraqi people were subjected to the most brutal crime in the history of humanity when ISIS violated the rights system and targeted women, children, civilians, minorities, religion, belief and the right to education and committed many crimes of genocide and crimes against humanity and the abandonment of millions of citizens and the recruitment of thousands of children, which constituted a flagrant violation of human rights and international law It emphasizes the gravity of the threat to international peace and security by the organization and its associated individuals, groups, institutions and entities, including foreign terrorist fighters.
That the legal characterization
... Show MoreMaximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.
The interest of this paper is that
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