Avinash Nehemiah, Product Marketing Manager for Computer Vision at MathWorks, presents the "How to Create a Great Object Detector" tutorial at the May 2014 Embedded Vision Summit.

Detecting objects of interest in images and video is a key part of practical embedded vision systems. Impressive progress has been made over the past few years by optimizing object detectors built on statistical machine learning methods. However, the pre-trained object detectors available today do not satisfy the increasing diversity of embedded vision system requirements.

This talk will teach you the basics of creating a robust and accurate object detector. Nehemiah covers the following topics:

  1. The importance of good training data sets
  2. The curse of dimensionality
  3. Overfitting (why too much training data is not a good thing), and
  4. How to select a classifier/detector based on the problem you are trying to solve.

Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.



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