A Generative Adversarial Transfer Learning Method Based on Sketch Annotation Information
A technology of labeling information and transfer learning, applied in the field of cross-domain image classification, which can solve the problem of inability to judge the invariant features of the feature domain.
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[0073]The present invention provides a generation confrontational transfer learning method based on sketch annotation information, which acquires an initial sketch map and constructs a paired data set in the form of "source domain image-source domain image edge annotation map"; constructs an edge based on sketch annotation information Segment and train the deep network; select target domain samples based on matrix norm; construct and train a generation-adversarial transfer learning network based on sketch annotation information, which includes a deep generator network, a deep discriminator network, and an edge segmentation depth based on sketch annotation information Network and deep classifier network; input the target domain image, and obtain the classification result of the target domain image; the present invention utilizes the similarity of the source domain data and the target domain data structure, and through structural constraints, generates samples that conform to the ...
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Abstract
Description
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Application Information
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