Tag: constraints
16. Learning: Support Vector Machines
Decision boundaries Separating positive and negative example with a straight line that is as far as possible from both positive and negative examples, a median that maximizes the space between positive and negative examples. Constraints are applied to build a support vector (u) and define a constant b that allow to sort positive examples from…
10. Introduction to Learning, Nearest Neighbors
Learning Regularity: “Bulldozer computing” Nearest neighbors: pattern recognition Neural nets: mimic biology Boosting: theory Constraints: human-like learning One-shot Explanation-based learning Nearest neighbor A detection mechanism generates a vector of features. These features are converted in a vector of values that is compared to a library of possibilities to find the closest match in order to…
9. Constraints: Visual Object Recognition
Borders and faces orientation Discerning borders of objects and face orientation with vectors, an initial computer vision theory seemed plausible but too difficult to implement. Orthographic projection In orthographic projection, the correspondence of a system of points of three known objects and one unknown object creates a system of equations with a unique solution of…
8. Constraints: Search, Domain Reduction
https://www.youtube.com/watch?v=d1KyYyLmGpA Domain Reduction Algorithm Vocabulary Variable v: something that can have an assignment Value x: something that can be assigned Domain d: set of all different values Constraint c: limit on variable values With a depth-first search, the domain reduction algorithm goes back up one node when it is unable to comply with a constraint. It…
7. Constraints: Interpreting Line Drawings
Computer vision Empirical approach Using lines on pictures of real-world objects, the edges between shapes could serve to identify the number of objects in it. The different intersections possible generally form two types of trihedral vertexes to identify shapes: arrow vertexes fork vertexes Theoretical approach A second approach uses convex and concave lines and boundaries…