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   图像描述模型 在 计算机软件及计算机应用 分类中 的翻译结果: 查询用时:0.087秒
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图像描述模型
相关语句
  image description model
    In this image description model, image contents could be analyzed and represented through different levels and the transition from low-level features to high-level semantics is thus achieved.
    该图像描述模型通过在不同层次上对图像内容进行分析和描述,实现了从低级特征到高级语义的过渡。
短句来源
  image description model
    In this image description model, image contents could be analyzed and represented through different levels and the transition from low-level features to high-level semantics is thus achieved.
    该图像描述模型通过在不同层次上对图像内容进行分析和描述,实现了从低级特征到高级语义的过渡。
短句来源
  image description model
    In this image description model, image contents could be analyzed and represented through different levels and the transition from low-level features to high-level semantics is thus achieved.
    该图像描述模型通过在不同层次上对图像内容进行分析和描述,实现了从低级特征到高级语义的过渡。
短句来源
  “图像描述模型”译为未确定词的双语例句
    4. For image feature description; firstly we set up a model of image features descriptors and image description, using XML & RDF languages to describe the image, and then we set up a trial modeling system and finally to retrieval image based on color, texture and shape.
    (4)在图像特征描述方面:我们给出图像特征描述符和图像描述模型,使用XML和RDF语言对图像进行描述。
短句来源
    In this paper, a novel system for content-based image retrieval is designed and created, which combines image semantics based on a multi-level model for image description.
    该系统利用了一个多级图像描述模型将语义特征结合到图像检索技术中。
短句来源
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Most existing content-based image retrieval systems using low-level features that could not describe high-level semantics thoroughly and accurately. In this paper, a novel system for content-based image retrieval is designed and created, which combines image semantics based on a multi-level model for image description. In this image description model, image contents could be analyzed and represented through different levels and the transition from low-level features to high-level semantics is thus achieved....

Most existing content-based image retrieval systems using low-level features that could not describe high-level semantics thoroughly and accurately. In this paper, a novel system for content-based image retrieval is designed and created, which combines image semantics based on a multi-level model for image description. In this image description model, image contents could be analyzed and represented through different levels and the transition from low-level features to high-level semantics is thus achieved. Corresponding querying mechanism and feedback are also proposed based on this image model. Aiming at object semantics in image, this querying mechanism is much closer to human beings' understanding of image contents so that it provides a convenient and effective querying procedure. The feedback used in the system is a self-adaptive relevance feedback based on object descriptions, it permits to propose different querying schemes according to the different demands raised by various users, and thus optimal results could be refined.

为克服当前基于内容的图像检索技术中低级特征无法准确全面地描述高级语义的问题,该文设计和实现了一个基于目标高级语义特征的检索系统。该系统利用了一个多级图像描述模型将语义特征结合到图像检索技术中。该图像描述模型通过在不同层次上对图像内容进行分析和描述,实现了从低级特征到高级语义的过渡。在此模型的基础上还研究了相应的检索机制和反馈技术。该系统的检索机制定位于图像中目标的语义内容,与传统的图像检索系统相比更接近人对图像内容的理解,从而使检索过程更简便,检索效率也得到很大提高。基于目标描述的自适应相关反馈可针对不同用户的不同需求给出相应的检索方案,从而使检索结果得到优化。

 
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