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TOPIC-GUIDED MODEL FOR IMAGE CAPTIONING SYSTEM

机译:图像捕获系统的主题导向模型

摘要

Techniques are provided for training and operation of a topic-guided image captioning system. A methodology implementing the techniques according to an embodiment includes generating image feature vectors, for an image to be captioned, based on application of a convolutional neural network (CNN) to the image. The method further includes generating the caption based on application of a recurrent neural network (RNN) to the image feature vectors. The RNN is configured as a long short-term memory (LSTM) RNN. The method further includes training the LSTM RNN with training images and associated training captions. The training is based on a combination of: feature vectors of the training image; feature vectors of the associated training caption; and a multimodal compact bilinear (MCB) pooling of the training caption feature vectors and an estimated topic of the training image. The estimated topic is generated by an application of the CNN to the training image.
机译:提供了用于训练和操作主题导向的图像字幕系统的技术。实现根据实施例的技术的方法包括基于对图像进行卷积神经网络(CNN)的应用,为要字幕的图像生成图像特征向量。该方法还包括基于将递归神经网络(RNN)应用于图像特征向量来生成字幕。 RNN被配置为长短期记忆(LSTM)RNN。该方法还包括用训练图像和相关的训练字幕训练LSTM RNN。训练基于以下组合:训练图像的特征向量;和相关训练标题的特征向量;训练字幕特征向量和训练图像的估计主题的多峰紧凑双线性(MCB)合并。通过将CNN应用于训练图像来生成估计的主题。

著录项

  • 公开/公告号US2019340469A1

    专利类型

  • 公开/公告日2019-11-07

    原文格式PDF

  • 申请/专利权人 INTEL CORPORATION;

    申请/专利号US201716473898

  • 发明设计人 ZHOU SU;JIANGUO LI;ANBANG YAO;YURONG CHEN;

    申请日2017-03-20

  • 分类号G06K9/62;G06T11/60;G06K9/72;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 12:07:51

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