# Recognizer Types

Object Class Recognition supports three different types of recognizer. All three use neural networks but have different characteristics.

- The default recognizer is the `Generation1` recognizer. This was the sole type of recognizer in Media Server versions 12.3 and earlier. This type of recognizer is the fastest to train but the other recognizers provide equal or better accuracy and are much faster at run-time.
- `Generation2` recognizers offer the best accuracy, but take the longest to train. The training time is impractical on a CPU, so Micro Focus recommends that you train the recognizer on a machine with a supported GPU. You can use a trained `Generation2` recognizer with or without a GPU but Micro Focus recommends using a GPU for best performance. If you run recognition on a GPU, this type of recognizer is much faster than the `Generation1` recognizer, which allows you to set much shorter sample intervals.
- `Generation3` recognizers are the fastest at run-time, but accuracy is slightly lower than the `Generation2` recognizer.

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