会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明申请
    • Image retrieval systems and methods with semantic and feature based relevance feedback
    • 图像检索系统和方法具有基于语义和特征的相关性反馈
    • US20050055344A1
    • 2005-03-10
    • US10969308
    • 2004-10-20
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • G06T1/00G06F17/30
    • G06F17/30265G06F17/30256G06F19/00Y10S707/99933Y10S707/99934Y10S707/99935
    • An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.
    • 图像检索系统执行基于关键词和基于内容的图像检索。 用户界面允许用户使用关键字和示例图像的组合来指定查询。 根据输入查询,图像检索系统查找与查询中的关键字匹配的关键字和/或具有类似低级特征(如颜色,纹理和形状)的图像。 系统对图像进行排序并将其返回给用户。 用户界面允许用户识别与查询更相关的图像,以及与查询较少或不相关的图像。 用户可以选择通过从结果集中选择一个示例图像并在新查询中提交其低级特征来优化搜索。 图像检索系统监视用户反馈,并使用它来优化任何搜索工作,并训练自己以用于将来的搜索查询。 在所描述的实现中,图像检索系统将基于特征的相关性反馈和基于语义的相关性反馈无缝集成。
    • 4. 发明授权
    • Image retrieval systems and methods with semantic and feature based relevance feedback
    • 图像检索系统和方法具有基于语义和特征的相关性反馈
    • US07529732B2
    • 2009-05-05
    • US10900574
    • 2004-07-28
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • Wen-Yin LiuHong-Jiang ZhangYe Lu
    • G06F17/30
    • G06F17/30265G06F17/30256G06F19/00Y10S707/99933Y10S707/99934Y10S707/99935
    • An image retrieval system performs both keyword-based and content-based image retrieval. A user interface allows a user to specify queries using a combination of keywords and examples images. Depending on the input query, the image retrieval system finds images with keywords that match the keywords in the query and/or images with similar low-level features, such as color, texture, and shape. The system ranks the images and returns them to the user. The user interface allows the user to identify images that are more relevant to the query, as well as images that are less or not relevant to the query. The user may alternatively elect to refine the search by selecting one example image from the result set and submitting its low-level features in a new query. The image retrieval system monitors the user feedback and uses it to refine any search efforts and to train itself for future search queries. In the described implementation, the image retrieval system seamlessly integrates feature-based relevance feedback and semantic-based relevance feedback.
    • 图像检索系统执行基于关键词和基于内容的图像检索。 用户界面允许用户使用关键字和示例图像的组合来指定查询。 根据输入查询,图像检索系统查找与查询中的关键字匹配的关键字和/或具有类似低级特征(如颜色,纹理和形状)的图像。 系统对图像进行排序并将其返回给用户。 用户界面允许用户识别与查询更相关的图像,以及与查询较少或不相关的图像。 用户可以选择通过从结果集中选择一个示例图像并在新查询中提交其低级特征来优化搜索。 图像检索系统监视用户反馈,并使用它来优化任何搜索工作,并训练自己以用于将来的搜索查询。 在所描述的实现中,图像检索系统将基于特征的相关性反馈和基于语义的相关性反馈无缝集成。