Improving a model with Model feedback
The Model Feedback solution enables you to give feedback on your model's predictions and make improvements by using human verification. Depending on the use case, you can be successful with a training dataset that has only a few images. A larger annotated training set might be required to build a more accurate model. Using the Model Feedback solution, you can create a larger dataset through model assistance.
To install and configure the Model Feedback solution, see Model Feedback Solution
The workflow for continuous model improvement is as follows:
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Train the first version of your model (possibly with a small training dataset).
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Provide an unannotated dataset for the Model Feedback solution.
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The Model Feedback solution uses the current model. It starts human verification jobs to annotate a new dataset.
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Based on human feedback, the Model Feedback solution generates a manifest file that you use to create a new model.
