Depending on the objective of image recognition, we may write the following general steps:
- Camera inputs training data set creates a supervised learning model.
- An Un supervised model breaks in to collect unlabeled dataset through feature
- Machine learning through a supervised algorithm.
- 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.
- The same preprocessing in training
- The same feature extraction in training
- Feeding the features into