Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recognition and identity verification systems. Deep learning-based approaches have been shown through cross-sectional studies to improve recognition accuracy under diverse environmental and demographic conditions. Anti-counterfeiting (Anti-Spoofing) and real presence detection features integrated into systems have likewise enhanced system security against advanced attacks such as 3D masks, false images and videos, and Deepfake technology. Future trends point to the need to develop deep, multi-sensory and interpretable learning models, and adopt learning strategies based on limited data, while adhering to legal and ethical frameworks to ensure fairness andtransparency.
Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a
... Show MoreMaximizing the net present value (NPV) of oil field development is heavily dependent on optimizing well placement. The traditional approach entails the use of expert intuition to design well configurations and locations, followed by economic analysis and reservoir simulation to determine the most effective plan. However, this approach often proves inadequate due to the complexity and nonlinearity of reservoirs. In recent years, computational techniques have been developed to optimize well placement by defining decision variables (such as well coordinates), objective functions (such as NPV or cumulative oil production), and constraints. This paper presents a study on the use of genetic algorithms for well placement optimization, a ty
... Show MoreDetecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.
As we live in the era of the fourth technological revolution, it has become necessary to use artificial intelligence to generate electric power through sustainable solar energy, especially in Iraq and what it has gone through in terms of crises and what it suffers from a severe shortage of electric power because of the wars and calamities it went through. During that period of time, its impact is still evident in all aspects of daily life experienced by Iraqis because of the remnants of wars, siege, terrorism, wrong policies ruling before and later, regional interventions and their consequences, such as the destruction of electric power stations and the population increase, which must be followed by an increase in electric power stations,
... Show MoreIdentity crisis is a dominant literary theme, especially in most Arab women writers’ works. However, it has not been given enough attention from a linguistic point of view. By so doing, the current study intends to fill this gap by analyzing the identity crisis from a pragma-stylistic perspective by examining the writer's style in three purposely selected extracts from Diana Abu-Jaber’s novel Origin (2007). The study aims to examine the identity crisis by using pragmatic and stylistic tools and to explore the effects of Abu-Jaber’s stylistic choices on the readers of her work. To conduct this study, an eclectic model comprising Searle’s speech acts (1979), Brown and Levinson's politeness theory (1987), Leech's model of figur
... Show MoreThe marshes form large areas in southern Iraq, which are large water bodies, covered by reeds and papyrus plants. The marshes are characterized by distinctive physical elements, which have given them a unique and unique identity that can be clearly distinguished by the physical pattern. The physical environment derives its identity through a group Of inputs that interact with each other and represent both cultural and social inputs of the most important inputs that affect the formation of identity, and in the physical environment of the Marshlands many of the symbols that are associated with the collective memory of individuals, these symbols have value in the community Thus, the preservation of these symbols and inherited from one gener
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