Dieser Kurs vermittelt einen Überblick über die Grundlagen des Maschinellen Sehens an Hand der Extraktion von 3D-Information aus dem Stereokamerabild einer Szene.
The course aims to provide a foundation in artificial intelligence techniques for planning, with an overview of the wide spectrum of different problems and approaches, including their underlying theory and their applications.
We will present the state of the art energy minimization algorithms that are used to perform inference in modern artificial vision models: that is, efficient methods for obtaining the most likely interpretation of a given visual input. We will also cover the popular max-margin framework for estimating the model parameters using inference.
Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.
This course will present advanced topics in Artificial Intelligence (AI). We will begin by defining the term “software agent” and discussing how software agents differ from programs in general. We will then take a look at those problems in the field of AI that tend to receive the most attention.
A real Caltech course, not a watered-down version. This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications.
Programming a Robotic Car.
This course delivers a systematic overview of computer vision, emphasizing two key issues in modeling vision: space and meaning.
This course introduces the field of artificial intelligence (AI).
Introduction to Artificial Intelligence.