# Recognizer Types

Object Class Recognition supports several types of recognizer. All 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. Choose `Generation1` only if you need to train the recognizer on a CPU.

The training time for `Generation2`, `Generation3`, and `Generation4` recognizers is impractical on a CPU, so Micro Focus recommends that you train the following types of recognizer on a machine with a supported GPU. You can use a trained recognizer with or without a GPU but Micro Focus recommends using a GPU for best performance. If you run recognition on a GPU, `Generation2`, `Generation3`, and `Generation4` recognizers are all much faster than a `Generation1` recognizer, which allows you to set much shorter sample intervals.

- `Generation2` recognizers offer much better accuracy than a `Generation1` recognizer. `Generation2` recognizers were introduced in Media Server 12.4 and Micro Focus now recommends using `Generation4` recognizers instead.
- `Generation3` recognizers are the fastest at run-time, but accuracy is slightly lower than a `Generation2` or `Generation4` recognizer.
- `Generation4` recognizers offer the best accuracy, especially for recognizers that you train yourself. The `Generation4` recognizer type was introduced in Media Server 12.9.

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