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    • 10. 发明申请
    • IMAGE SIMILARITY AS A FUNCTION OF WEIGHTED DESCRIPTOR SIMILARITIES DERIVED FROM NEURAL NETWORKS
    • 图像相似性作为从神经网络衍生的称重描述符相似性的函数
    • US20160196479A1
    • 2016-07-07
    • US14987520
    • 2016-01-04
    • SUPERFISH LTD.
    • Michael CHERTOKAlexander LORBERT
    • G06K9/66G06K9/52G06K9/62
    • G06K9/4628G06K9/621G06K9/6272
    • A method for determining image similarity as a function of weighted descriptor similarities, including the procedures of feeding a query image to a network including a plurality of layers and defining an output of each of the layers as a descriptor of the query image, feeding a reference image to the network and defining an output of each of the layers as a descriptor of the reference image, determining a descriptor similarity score for respective descriptors that were produced by the same layer of the network fed the query image and the reference image, assigning a respective weight to each descriptor similarity score and defining an image similarity between the query image and the reference image as a function of the weighted descriptor similarity scores.
    • 一种用于确定作为加权描述符相似性的函数的图像相似度的方法,包括将查询图像馈送到包括多个层的网络并将每个层的输出定义为查询图像的描述符的过程,馈送参考 映射到网络并且将每个层的输出定义为参考图像的描述符,确定由馈送查询图像和参考图像的网络的相同层产生的各个描述符的描述符相似性得分, 相应于每个描述符相似性分数的权重,并且根据加权描述符相似性得分来定义查询图像和参考图像之间的图像相似度。