ROBUST TEST-TIME ADAPTATION WITHOUT ERROR ACCUMULATION

    公开(公告)号:US20240303497A1

    公开(公告)日:2024-09-12

    申请号:US18360712

    申请日:2023-07-27

    CPC classification number: G06N3/091 G06N3/045

    Abstract: A processor-implemented method for adapting an artificial neural network (ANN) at test-time includes receiving by a first ANN model and a second ANN model, a test data set. The test data set includes unlabeled data samples. The first ANN model is pretrained using a training data set and the test data set. The first ANN model generates first estimated labels for the test data set. The second ANN model generates second estimated labels for the test data set. Samples of the test data set are selected based on a confidence difference between the first estimated labels and the second estimated labels. The second ANN model is retrained based on the selected samples.

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