ADR Awareness Centre

A detailed introduction to computer vision will be made: image/video sampling, Image and video acquisition, Camera geometry, Stereo and Multiview imaging, Structure from motion, Structure from X, 3D Robot Localization and Mapping, Semantic 3D world m

This lecture overviews that has many applications in broadcasting archives abd video description, search, retrieval and browsing.

Provides a comprehensive overview of the representation learning techniques for natural language processing. Presents a systematic and thorough introduction to the theory, algorithms and applications of representation learning. Shares insights into

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.

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

This resource corresponds to 9th video from the AI Excellence Lecture Series. PAC-Bayesian Analysis is a framework in machine learning and statistics that combines ideas from the Probably Approximately Correct (PAC) learning framework and Bayesian p

This lecture overviews Video Captioning that has many applications in video description, search and retrieval. It covers the following topics in detail: Video captioning definitions and datasets.

This lecture overviews Soccer Video Analysis that has many applications in Human-centered Computing, Image and Video Analysis and Sports Analytics/coaching.

This lecture overviews Dimensionality Reduction that has many applications in object clusring and object recognition.  It covers the following topics in detail: Feature selection. Principal Component Analysis. Linear Discriminant Analysis.

Recent progress in the Computer Vision and Natural Language Processing communities have made it possible to connect Vision and Language together in a variety of different tasks which lie at the intersection of Vision, Language, and Embodied AI.

This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.

This lecture overviews Autonomous Car Sensors that has many applications in autonomous car perception.