Building a Content-Based Multimedia Search Engine II: Extracting Feature Vectors
This is part 2 in a series of tutorials in which we learn how to build a content-based search engine that retrieves multimedia objects based on their content rather than based on keywords, title or meta description. Part I: Quantifying [...]
Building a Content-Based Multimedia Search Engine I: Quantifying Similarity
This is part 1 in a series of tutorials in which we learn how to build a content-based search engine that retrieves multimedia objects based on their content rather than based on keywords, title or meta description. Part I: Quantifying [...]
Deep Learning From Scratch VI: TensorFlow
This is part 6 of a series of tutorials, in which we develop the mathematical and algorithmic underpinnings of deep neural networks from scratch and implement our own neural network library in Python, mimicing the TensorFlow API. Start with the first [...]
Connectionist Models of Cognition
In this video, I give an introduction to the field of computational cognitive modeling (i.e. modeling minds through algorithms) in general, and connectionist modeling (i.e. using artificial neural networks for the modeling) in particular. We deal with the following topics:The purpose [...]
Robot Localization IV: The Particle Filter
This is part 4 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation The last [...]
Robot Localization III: The Kalman Filter
This is part 3 in a series of articles explaining methods for robot localization, i.e. determining and tracking a robot's location via noisy sensor measurements. You should start with the first part: Robot Localization I: Recursive Bayesian Estimation This post [...]