Depending on the objective of image recognition, we may write the following general steps:
Training

  1. Camera inputs training data set creates a supervised learning model.
  2. Preprocessing.
  3. An Un supervised model breaks in to collect unlabeled dataset through feature
    extraction.
  4. Machine learning through a supervised algorithm.
  5. After checking results on how good it recognizes, if it takes more data to learn
    properly. Go to step 1 and repeat the process again.
    Recognition:
  6. The same preprocessing in training
  7. The same feature extraction in training
  8. Feeding the features into
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