Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this aspect of the Deepfake detection task and proposes pre-processing steps to improve accuracy and close the gap between training and validation results with simple operations. Additionally, it differed from others by dealing with the positions of the face in various directions within the image, distinguishing the concerned face in an image containing multiple faces, and segmentation the face using facial landmarks points. All these were done using face detection, face box attributes, facial landmarks, and key points from the MediaPipe tool with the pre-trained model (DenseNet121). Lastly, the proposed model was evaluated using Deepfake Detection Challenge datasets, and after training for a few epochs, it achieved an accuracy of 97% in detecting the Deepfake
Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network
... Show More This paper concerns with openness concept in contemporary learning environment, which ranges from physical characters to its relation with learning efficiency and its output. Previous literatures differ to clear the effect of openness on the engagement between learner within themselves, and with this kind of spaces. Engagement means: active participation, the ability of making dialogue, self-reflection and the ability to explore and communicate with them and
within learning space. Research roblem was: The lack of knowledge about the effect of Openness on learner engagement with learning spaces. The two concepts were applied on three types of learning spaces in the Department of the Architectu
The aim of this research is to identify the effect of Webinar technique on digital culture in the College of Education for pure sciences at Ibin Haitham, University of Baghdad. The research samples consisted of (68) male and female students from the Chemistry Department who are following classes during the (2019- 2020) academic year. The samples represent (42%) of the total number of (162) students split into control and experimental groups. For this purpose, the scientific contents for testing were determined. The experimental part is based on analysis of the results from experiments in (preliminary standard solutions, refractive index, Beer-Lambert law). To achieve the aim of the research in testing the measure of student's digital cultur
... Show MoreThe communication inspiration formed an essential foundations for contribute the influence individuals and recipients, whether negatively or positively, through the messages that were published and presented in them with multiple themes and viewpoints that covered all parts of the world and all age groups; it is directed to children addressing the various stages of childhood, as it simulates many goals, including what is directed through the digital use of educational data in television production, as it is considered an intellectual and mental bag to deliver ideas and expressive and aesthetic connotations to children, where the songs and cartoons carrying data on education; within adjacent relations and in a mutual direction, both of th
... Show MoreDigital commercial advertising depends on artistic formations to achieve attraction and arousal of attention, which is one of the most important communication factors that the designer seeks to achieve and is considered a key key to recognizing the beauty of the topic and its functional value. Reframe formal vocabulary.
The research included the introduction and includes the research problem and the need for it, which focused on the following question: What is the aesthetic role of artistic formation in the design of commercial advertising?
The aim of the research was: To reveal the aesthetic role of artistic formation in commercial advertising.
It also included the importance of research and research boundaries, as well as def
NAA Mustafa, University of Sulaimani, Ms. c Thesis, 2010 - Cited by 4
Embracing digital technological advancements in media and communication has led government entities to adopt communication practices fully aligned with the digital and networked system in government communication. Traditional media practices within the government environment increasingly rely on the ability to utilize digital tools and systems for content creation, communication, evaluation, and the management of the entire communication process within an electronic and intelligent framework for government services. Naturally, this transformation has caught the attention of communication and public relations researchers worldwide, as the digital and networked aspects of government communication now form an intelle
... Show MoreThe financial fraud considers part of large concept to management and financial corruption, the financial fraud is appeared especially after corporate, that is Emerge agency theory, that is because recognize relationship between the management company and stakeholder, that is through group from constriction in order to block the management to fraud practice, that on the basis was choose another party in order fraud this practice and give opinion on financial statement, that consider basis decision making from stakeholder to basis the report auditor about creditability this is statement that reflect real activity for the company.The Auditor in order to lead work him Full professionalism to must using group from control Techniques, that is
... Show MoreThe concealment of data has emerged as an area of deep and wide interest in research that endeavours to conceal data in a covert and stealth manner, to avoid detection through the embedment of the secret data into cover images that appear inconspicuous. These cover images may be in the format of images or videos used for concealment of the messages, yet still retaining the quality visually. Over the past ten years, there have been numerous researches on varying steganographic methods related to images, that emphasised on payload and the quality of the image. Nevertheless, a compromise exists between the two indicators and to mediate a more favourable reconciliation for this duo is a daunting and problematic task. Additionally, the current
... Show MoreThis paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance
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