A comprehensive time series analysis project that uses various forecasting techniques to predict book sales and demand patterns. This project analyzes historical sales data from Nielsen BookScan to ...
In the fast-moving digital landscape, where gig workers expect instant payouts and companies handle millions of microtransactions daily, the need for robust real-time fraud detection has never been ...
Abstract: Current defense mechanisms against model poisoning attacks in federated learning (FL) systems have proven effective up to a certain threshold of malicious clients (e.g., 25% to 50%). In this ...
Abstract: Detecting anomalies in time-series data is essential for identifying outliers and issuing early warnings of system failures in applications such as Industrial Control Systems (ICS), Internet ...
Cybersecurity researchers have charted the evolution of XWorm malware, turning it into a versatile tool for supporting a wide range of malicious actions on compromised hosts. "XWorm's modular design ...
A comprehensive computer vision project for detecting and analyzing Iranian supermarket snacks and chips using YOLOv11 object detection and segmentation models. This system combines real-time object ...
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