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    Novel Deepfakes Detection Strategies: Insights from Prosopagnosia
    (Newcastle University, 2024-10) Alanazi, Fatimah; Morgan, Graham
    The credibility of audio and video content, which is essential to our perception of reality, is increasingly challenged by advancements in deepfake generation techniques. Existing detection models primarily focus on identifying anomalies and digital artifacts. However, the rapid evolution of technology enables the creation of sophisticated deepfakes that can evade these methods. This thesis investigates the effectiveness of different facial features for deepfake detection in images and face recognition in individuals with prosopagnosia. It examines whether there is a correlation between the facial features prioritized by AI models for deepfake detection and those emphasized in training programs aimed at enhancing face recognition in individuals with prosopagnosia. Additionally, it assesses the impact of occluding each facial feature during training on AI model performance and identifies which facial elements individuals with prosopagnosia find most challenging to recognize. Inspired by research into prosopagnosia, which highlights the importance of internal facial features like the eyes and nose, this study proposes a novel approach to deepfake detection. The methodology involves identifying critical facial features, applying face cut-out techniques to create training images with various occlusions, and evaluating AI models trained on these datasets using EfficientNet-B7 and Xception models. The results indicate that models trained with occluded datasets performed better, with the EfficientNet-B7 model achieving a higher accuracy rate (92%) when core facial elements (eyes and nose) were covered, compared to models trained on datasets without occlusions or with occlusions covering external features. This suggests that focusing on features outside the face’s center improves detection accuracy. The findings also highlight that facial cues beneficial for individuals with prosopagnosia do not uniformly translate to equivalent value for AI models. This research demonstrates that detection systems can be more effective by focusing on a small region of the face, contributing significantly to the improvement of deepfake detection methods and enhancing our understanding of face recognition processes.
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    The Role of Riyadh Season in Promoting Tourism: A Comparative Study of Visitor Experiences
    (Leeds Beckett University, 2024-06-27) Alanazi, Fatimah; Moss, Jonathan
    The research investigates Riyadh Season's impact on tourism promotion in Saudi Arabia, exploring visitors' experiences and perceptions. Saudi Arabia, transitioning from oil reliance, prioritizes tourism growth through Vision 2030 initiatives. Riyadh Season, a significant event, attracts diverse visitors, driving economic and cultural development. The study aims to compare Riyadh Season's effectiveness with theoretical frameworks like competitiveness theory, social exchange theory, destination marketing, local branding, cultural tourism theory and other events. By using these theories its historical significance is assessed, and visitors' experiences are understood. Through a quantitative approach, the research utilizes secondary literature and a survey to analyze Riyadh Season's influence on tourism and its connections to visitors' perceptions. Findings suggest Riyadh Season positively impacts tourism, attracting visitors with its cultural richness and diverse offerings. Social media emerges as a key communication channel, strengthening event visibility and engaging visitors. Additionally, promoting positive interactions between tourists and locals enhances destination competitiveness and visitor satisfaction. Recommendations include expanding research to include non- Saudi national perspectives, enriching the understanding of Riyadh Season's international perception. Ultimately, the study contributes to Saudi Arabia's tourism strategy, highlighting Riyadh Season's role in shaping the nation's tourism landscape and promoting international engagement.
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