GAN-based data enhancement unsupervised trademark retrieval system and method
A retrieval system and unsupervised technology, applied in the field of artificial intelligence, can solve problems such as difficult data labeling and insufficient collection
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Embodiment 1
[0041] An unsupervised trademark retrieval system based on GAN data enhancement, including a GAN data enhancement module, an instance distinction module, and a trademark retrieval module, wherein the GAN data enhancement module is used to enhance the trademark data set and expand the trademark training set; the instance distinction training module uses To train the unsupervised network to obtain the trademark feature extractor; the trademark retrieval module is used to calculate the similarity measure between the trademark database and the trademark features to be retrieved, and output the ranking results of the trademarks.
[0042]In a preferred solution, the GAN data enhancement module generates a trademark data set through a trained GAN model, and combines the enhanced trademark data set with the original trademark data set to form a new trademark database M .
[0043] In a preferred solution, the training steps of the GAN model are as follows:
[0044] Step 1. Keeping the...
Embodiment 2
[0060] A GAN-based data-enhanced unsupervised trademark retrieval method, applied to the above-mentioned system, includes the following steps:
[0061] S1. The GAN data enhancement module is used to enhance the trademark data set, expand the trademark training set, and obtain a new trademark database;
[0062] S2. The example distinguishing training module trains the unsupervised network, obtains the trademark feature extractor, and extracts the image features of the trademark to be retrieved;
[0063] S3. The trademark retrieval module calculates the similarity measure between the trademark database and the characteristics of the trademark to be retrieved, and outputs the ranking result of the trademark.
[0064] In a preferred solution, the GAN data enhancement module generates a trademark data set through a trained GAN model, and combines the enhanced trademark data set with the original trademark data set to form a new trademark database M .
[0065] In a preferred solut...
Embodiment 3
[0082] The invention provides a trademark retrieval method. Using ResNet50 as an unsupervised network, in the instance discrimination mode, the trademark data set is generated by the trained GAN model to generate a data set Q, and the data set Q is added to the original trademark data set to form a new trademark data set M, and finally passed The new trademark data set M is used to train the instance discrimination module to obtain the trademark feature extractor ResNet50. In the retrieval module, the new trademark data set M is extracted through the trained trademark feature extractor ResNet50 to form a trademark feature library F={F 1 , F 2 ,...,F n}. Similarly, the image to be retrieved is passed through the trained trademark feature extractor ResNet50 to extract the feature F', and finally, the similarity measure between the trademark database and the retrieved image is calculated according to the Euclidean distance, and sorted according to the size of the similarity me...
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