CPC G06V 10/82 (2022.01) [G06F 18/41 (2023.01); G06V 10/7788 (2022.01)] | 20 Claims |
1. A method of using pre-trained neural networks to train classifiers to classify images, the method comprising:
providing a plurality of genealogical images to an image classifier; and
for a genealogical image of the plurality of genealogical images:
creating a feature vector for the genealogical image using a feature extractor of the image classifier, wherein the feature extractor includes a pre-trained neural network previously trained to extract feature vectors from images within a non-genealogical image database;
based on the feature vector created using the feature extractor trained on the non-genealogical image database, assigning a label to the genealogical image using a feature classifier of the image classifier, wherein the feature classifier is separate from the feature extractor and the pre-trained neural network;
receiving a corrected label for the genealogical image;
determining an error between the label and the corrected label; and
adjusting the feature classifier to improve classification of genealogical images based on the error without adjustment to the feature extractor and the pre-trained neural network.
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