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首页> 外文期刊>Multimedia, IEEE Transactions on >Image Classification by Cross-Media Active Learning With Privileged Information
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Image Classification by Cross-Media Active Learning With Privileged Information

机译：通过具有特权信息的跨媒体主动学习进行图像分类

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摘要

In this paper, we propose a novel cross-media active learning algorithm to reduce the effort on labeling images for training. The Internet images are often associated with rich textual descriptions. Even though such textual information is not available in test images, it is still useful for learning robust classifiers. In light of this, we apply the recently proposed supervised learning paradigm, learning using privileged information, to the active learning task. Specifically, we train classifiers on both visual features and privileged information, and measure the uncertainty of unlabeled data by exploiting the learned classifiers and slacking function. Then, we propose to select unlabeled samples by jointly measuring the cross-media uncertainty and the visual diversity. Our method automatically learns the optimal tradeoff parameter between the two measurements, which in turn makes our algorithms particularly suitable for real-world applications. Extensive experiments demonstrate the effectiveness of our approach.
机译：在本文中，我们提出了一种新颖的跨媒体主动学习算法，以减少标记图像进行训练的工作量。 Internet图像通常与丰富的文本描述相关联。即使这样的文本信息在测试图像中不可用，对于学习鲁棒的分类器仍然有用。有鉴于此，我们将最近提出的监督学习范式（使用特权信息进行学习）应用于主动学习任务。具体来说，我们在视觉特征和特权信息上训练分类器，并通过利用学习到的分类器和松弛函数来测量未标记数据的不确定性。然后，我们建议通过共同测量跨媒体不确定性和视觉多样性来选择未标记的样本。我们的方法会自动学习两次测量之间的最佳折衷参数，从而使我们的算法特别适合于实际应用。大量的实验证明了我们方法的有效性。

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  • 来源
    《Multimedia, IEEE Transactions on》 |2016年第12期|2494-2502|共9页
  • 作者

    Yan Yan; Feiping Nie; Wen Li; Chenqiang Gao; Yi Yang; Dong Xu;

  • 作者单位

    Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia;

    Center for Optical Imagery Analysis and Learning, Northwestern Polytechnical University, Xi’an, China;

    Computer Vision Laboratory, ETH Zurich, Zurich, Switzerland, CH;

    School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, China;

    Centre for Quantum Computation and Intelligent Systems, University of Technology Sydney, Sydney, NSW, Australia;

    School of Electrical and Information Engineering, University of Sydney, Sydney, NSW, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Uncertainty; Training; Measurement uncertainty; Visualization; Internet; Data models; Electronic mail;

    机译：不确定度;培训;测量不确定度;可视化;互联网;数据模型;电子邮件;

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