Displaying 265 resources
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Geometric data analysis based on manifold learning with applications for image understanding

The conference paper gives in the first section a brief and easy understandable introduction into the basics of Riemannian geometry.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Case studies Case studies
White paper White paper

Terse notes on Riemannian geometry

The technical report gives a compact introduction into the basic definitions and theorems of Riemannian geometry, Lie groups & Lie algebras and symmetric spaces.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Case studies Case studies
White paper White paper

Learning on manifolds

The conference paper provides a brief introduction into manifolds from a computer vision perspective. Important manifolds for this research field, like symmetric positive definite matrices and affine transformation matrices, are presented.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Article/Books/eBooks Article/Books/eBooks

An introduction to manifolds

This book provides an introduction to the theory of manifolds in an easy readable way. Key concepts of manifolds, angent spaces and Lie group / Lie algebra are presented.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Certification Certification
Online Course Online Course
Video/Webinars Video/Webinars

From Images to Text New forms of Human-AI Interaction

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.

Category
Systems, methodologies, hardware, and tools
Source
AI-OnDemand
Case studies Case studies
White paper White paper

Representation Learning for Natural Language Processing

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.

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