ADR Awareness Centre

This lecture will overview 2D linear and cyclic convolution. Then it will present their fast execution through FFTs, resulting in algorithms having computational complexity of the order O(N^2log2N).

This lecture overviews Graph Neural Networks that has many applications in Deep Learning, Signal and Video Analysis, Network Theory, Web Science and Social Media Analytics. It covers the following topics in detail: Introduction to Graphs.

The survey provides a comprehensive overview of deep learning methods for geometric data (point clouds, voxels, network graphs etc.). The relevant knowledge and theoretical background of geometric deep learning is presented first.

Convolutional Neural Networks form the backbone of current AI revolution and are used in a multitude of classification and regression problems. This lecture overviews the transition from multilayer perceptrons to deep architectures.

This lecture overviews ECG Signal Analysis as well as other cardiology imaging methods that has many applications in cardiological disorder diagnosis and treatment. It covers the following topics in detail: Background nnowledge of ECG Signals.

This lecture overviews various concepts related to multiple drone communications: LTE and WiFi communications, LTE communication infrastructure, IP network issues, Security analysis, throughput, latency and quality-of-service issues.

This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation.

This lecture overviews Neural Image Compression that has many applications in image storage and communications.

This lecture overviews Pedestrian Detection  that has many applications in autonomous car vision and smart city applications.

1D convolutions are extensively used in digital signal processing (filtering/denoising) and analysis (also through CNNs).  As their computational complexity is of the order O(N^2), their fast execution is a must. This lecture will overview

Cloud Computing during the time has gained concrete evidence to be a disruptive technology still in its full development. Many drawbacks of the Cloud have brought to improve many their crucial aspects, like performance, security and privacy, etc.

Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.