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Zero-shot sketch-based image retrieval techniques using neural networks for sketch-image recognition and retrieval

机译:基于神经网络的零镜头基于草图的图像检索技术,用于草图图像的识别和检索

摘要

This disclosure relates to improved sketch-based image retrieval (SBIR) techniques. The SBIR techniques utilize an architecture comprising three interconnected neural networks to enable zero-shot image recognition and retrieval based on free-hand sketches. Zero-shot learning may be implemented to retrieve one or more images corresponding to the sketches without prior training on all categories of the sketches. The neural network architecture may do so, at least in part, by training encoder hashing functions to mitigate heterogeneity of sketches and images, and by applying semantic knowledge that is learned during a limited training phase to unknown categories.
机译:本公开涉及改进的基于草图的图像检索(SBIR)技术。 SBIR技术利用包括三个相互连接的神经网络的体系结构,以实现基于徒手草图的零镜头图像识别和检索。零射学习可以被实现为检索与草图相对应的一个或多个图像,而无需事先对草图的所有类别进行训练。神经网络体系结构可以至少部分地通过训练编码器散列函数来减轻草图和图像的异质性,以及通过将在有限的训练阶段中学到的语义知识应用于未知类别来做到这一点。

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