Displaying 83 resources
Imaging for Drone Safety
This lecture overviews Imaging for Drone Safety that has many applications in autonomous drones.
Tutorial paper on Deep Learning for Graphs
The adaptive processing of graph data is a long-standing research topic that has been lately consolidated as a theme of major interest in the deep learning community.
Continuous-time Signals and Systems
This lecture overviews continuous-time Signals and Systems topics. Continuous-time signals are presented: periodic signals, delta function, unit step signal, exponential signal, trigonometric signals, complex exponential signal.
Road Condition Assessment
This lecture overviews Road Condition Assessment that has many applications in autonomous car perception and smart city management. It covers the following topics in detail:
1D Convolutional Neural Networks
This lecture overviews 1D Convolutional Neural Networks that has many applications in 1D signal analysis.
Introduction to Autonomous Systems
A fully autonomous system can: a) gain information about the environment, b) work for an extended period without human intervention, c) move either all or part of itself throughout its operating environment without human assistance and d) avoid situa
Statistical Detection
This lecture overviews Statistical Detection that has many applications in Machine Learning, Signal Analysis and Statistical Communications.
Laplace Transform
This lecture presents Laplace Transform (LT) and its region of convergence. Its relation to Laplace transform is presented. Notable LT properties are reviewed: time shift, convolution, signal differentiation/integration.
Z Transform
This lecture overviews Z Transform that has many applications in signal processing and systems theory.
Attention and Transformers Networks
In this lecture, the limitations of Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs) in effectively processing sequences are emphasized.
Artificial Neural Networks. Perceptron
This lecture will cover the basic concepts of Artificial Neural Networks (ANNs): Biological neural models, Perceptron, Activation functions, Loss types, Steepest Gradient Descent, On-line Perceptron training, Batch Perceptron training.
Self-awareness for autonomous systems
Self-awareness is a broad concept borrowed from cognitive science and psychology that describes the property of a system, which has knowledge of “itself,” based on its own senses and internal models.