HYBRID CLASSIFIER TRAINING FOR FEATURE ANNOTATION

    公开(公告)号:US20240428561A1

    公开(公告)日:2024-12-26

    申请号:US18707558

    申请日:2022-11-04

    Abstract: The use of machine learning (ML) can provide good results in annotating features present in images. However training the ML process can require a large amount of training images that have had the individual features correctly annotated. An ML process and training technique is described that can train and use a classifier in order to annotate features in an image. The training uses saliency loss propagation (SLP) to train the classifier on portions of images that include important features.

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