Abstract: This work proposes a novel neural network-based framework to address the critical task of predicting the electromagnetic compatibility of satellite navigation systems. The proposed framework ...

Abstract: Deep learning models are highly susceptible to adversarial attacks, where subtle perturbations in the input images lead to misclassifications. Adversarial examples typically distort specific ...

A comprehensive machine learning web application for predicting future locations based on temporal movement patterns. Built with Streamlit, this system provides an interactive interface for data ...

Track delivery vehicles across cities in real-time. Monitor route adherence, delivery times, and fuel consumption. Get alerts when vehicles deviate from geofenced zones or when drivers speed. Manage a ...