Displaying 103 resources
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ECG Signal Analysis

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.

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Fast 3D Convolution algorithms

This lecture overviews Fast 3D Convolution algorithms that has many applications in the fast implementation of 3D image and video filtering, 3D CNNs and motion estimation.

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Fast 1D Convolution Algorithms

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.

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Graph Neural Networks

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.

Category
Data for AI
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

Adversarial Machine Learning

This lecture overviews Adversarial Machine Learning that has many applications in DNN robustness and in privacy protection.

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Tutorial/How To/Guides Tutorial/How To/Guides

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.

Category
Data for AI, Systems, methodologies, hardware, and tools
Source
AI-OnDemand