Geometric Feature Learning

Geometric Feature Learning

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Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Geometric feature learning is a technique combining machine learning and computer vision to solve visual tasks. The main goal of this method is to find a set of representative features of geometric form to represent an object by collecting geometric features from images and learning them using efficient machine learning methods. Humans solve visual tasks and can give fast response to the environment by extracting perceptual information from what they see. Researchers simulate humans' ability of recognizing objects to solve computer vision problems. For example, M. Mata applied feature learning techniques to the mobile robot navigation tasks in order to avoid obstacles. They used genetic algorithms for learning features and recognizing objects. Geometric feature learning methods can not only solve recognition problems but also predict subsequent actions by analyzing a set of sequencial input sensory images, usually some extracting features of images.
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Product details

  • Paperback | 96 pages
  • 152 x 229 x 6mm | 150g
  • The
  • United States
  • English
  • black & white illustrations
  • 6136431653
  • 9786136431659