Seven measures to improve the accuracy of AI.

The challenge after creating an AI model is "improving accuracy."

In recent years, tools and services that allow for the easy creation of Deep Learning models have been made available. With this ease of access, there are likely already individuals who have begun developing Deep Learning models. The next challenge after creating a Deep Learning model is "improving accuracy." When the expected accuracy is not achieved, the following actions can lead to performance improvements: 1. Change various hyperparameters. 2. Increase the amount of training data. 3. Increase the "patterns" in the training data. For example, differences in lighting brightness, size, and speed. 4. Perform preprocessing to clarify the features of the data. 5. Compare and consider multiple types of models to use. 6. Review the class design of the model. 7. Build an ensemble model that combines multiple models. However, carrying out these tasks requires specialized knowledge, as well as time and effort to prepare the data. By using our "DeepEye," you can easily implement these accuracy improvement strategies.

Other Software