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SKETCH-BASED IMAGE RETRIEVAL TECHNIQUES USING GENERATIVE DOMAIN MIGRATION HASHING

机译:基于草图的图像检索技术,使用生成域迁移散列

摘要

This disclosure relates to improved sketch-based image retrieval (SBIR) techniques. The SBIR techniques utilize a neural network architecture to train a domain migration function and a hashing function. The domain migration function is configured to transform sketches into synthetic images, and the hashing function is configured to generate hash codes from synthetic images and authentic images in a manner that preserves semantic consistency across the sketch and image domains. The hash codes generated from the synthetic images can be used for accurately identifying and retrieving authentic images corresponding to sketch queries, or vice versa.
机译:本公开涉及改进的基于草图的图像检索(SBIR)技术。 SBIR技术利用神经网络架构来训练域迁移函数和散列函数。域迁移函数被配置为将草图转换为合成图像,并且散列函数被配置为以保留草图和图像域的语义一致性的方式生成散列码和真实图像。从合成图像生成的散列码可用于准确识别和检索与草图查询相对应的真实图像,反之亦然。

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