[ad_1] Introduction Traffic accidents are a major concern worldwide, causing a significant number of fatalities and injuries each year. Predicting traffic accidents can help in preventing them, reducing their severity, and improving road safety. Deep…
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[ad_1] Introduction Facial recognition for emotion detection using computer vision and deep learning has garnered significant interest in recent years due to its wide range of applications in various fields such as healthcare, security, and…
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[ad_1] Introduction As online transactions continue to grow in popularity, so does the risk of fraud. Fraudulent activities such as identity theft, account takeover, and payment fraud pose a significant threat to both businesses and…
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[ad_1] Introduction Predictive modeling for energy consumption using time series analysis and machine learning is a critical area of research that has gained significant attention in recent years. As the demand for energy continues to…
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[ad_1] Introduction: Image segmentation is a crucial task in medical image analysis, as it plays a vital role in various clinical applications such as tumor detection, organ segmentation, and disease classification. Deep learning algorithms have…
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[ad_1] **Introduction** In recent years, the proliferation of online hotel reviews has provided a valuable resource for both travelers seeking information and hotels wanting to assess customer satisfaction. Sentiment analysis, a subfield of natural language…
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[ad_1] Introduction The rapid development of the Internet of Things (IoT) has led to the deployment of a large number of sensor devices in various environments, such as smart homes, smart cities, and industrial settings.…
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[ad_1] Thesis Overview: Title: Sentiment analysis of customer feedback using text mining and machine learning Introduction: Sentiment analysis is the process of extracting and analyzing subjective information from text data, to determine the sentiment or…
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[ad_1] Introduction Social network analysis (SNA) is a powerful tool that leverages network theory and data analysis techniques to study the structure and behavior of networks. In recent years, SNA has gained increasing attention in…
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[ad_1] Introduction: In recent years, the use of predictive modeling for credit risk assessment has gained significant attention in the financial industry. This approach allows financial institutions to analyze historical data and predict the creditworthiness…
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