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基于内容的图像检索，里面也包含了图像语义方面的内有，比如关键字的提取 特征向量的提取等待,Content-based Image Retrieval, which also contains images, there are semantic aspects, such as keyword extraction extraction eigenvector wait
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本文以基于内容的图像检索为主，对检索系统的关键技术特别是图像特征提
取方面做了深入的研究。提出了一种结合图像颜色特征与图像语义特征的图像检
索新方法，克服了单纯的基于内容图像检索未曾考虑图像内容特征与其语义之间
鸿沟的缺点。-This dissertation briefly summarizes CBIR system，and researches some key
techniques of the image retrieval which specially focuse
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随着数字图象技术、宽带网络技术和数字存储设备技术的发展，在网络上存储、传输大规模分布式数字图象库
成为可能，因此研究基于内容的图象检索技术成为近几年的热点。实现基于内容的图象检索系统的关键问题是实现图象
的语义分割。该文分六类对现有的图象语义分割技术进行了全面的总结，为进一步研究基于内容的图象检索技术奠定了
基础。-With the digital image technology, broadband networks and digital storage device tech
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图像检索的的基于语义的图像检索 纹理图像检索 图像的特征提取方法-Image Retrieval of semantic-based image retrieval image retrieval image texture feature extraction methods
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毕业设计之用的，功能全面的基于语义的图像检索程序，希望对大家提供帮助。-Designed graduation purposes, full-featured semantic-based image retrieval procedures, and they hope to help everyone.
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这是关于语义图像检索进展的一片论文，很好的综述性文章，希望研究图像语义的朋友一起学习- Semantic image retrieval has been a crux to bridge“semantic gap”between the simple
visual features and the abundant semantics delivered by an image. The state of the art of semantic
image retrieval is g
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The various tasks described above—content-based image retrieval, object-level image subregion
querying, object localization, cut detection, and semantic organization of an image collection —
become especially challenging when the image database i
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aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of
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aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context
people s names and facia
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aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of
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0下载：
aleix@ecn.
Semantic queries to a database of images are more
desirable than low-level feature queries, because they
facilitate the user s task. One such approach is the
object-related image retrieval. In the context of face
images, it is of
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一篇EI英文论文，有关图像检索语义方面的。-a novel semantic image retrieval methd
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基于不同特征的图像检索技术，颜色、纹理、形状、空间关系等特征提取的基础上，基于语义的图像检索技术-Different characteristics based image retrieval, color, texture, shape, spatial relations, feature extraction based on semantic-based image retrieval. Rar
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这儿是关于图像检索的资料和代码。也有我自己写的程序。关于聚类的
-Here is information on image retrieval and code. Have to write my own program. About Clustering
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In this research two automatic video annotation techniques are considered. The first technique uses ontology to reduce the semantic gap during video retrieval and other performs a group based image retrieval using video files. The proposed algorithm
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基于内容的图像检索 基于颜色、纹理、形状的图像检索
基于区域的图像检索
基于语义的图像检索
相关反馈
-Based on the content-based image retrieval based on color, texture, shape-based image retrieval region-based image retrieval based on semantic image retrieval relevance feedback
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Photos with people (e.g., family, friends, celebrities, etc.) are the major interest of users. Thus, with the exponentially growing photos, large-scale content-based face image retrieval is an enabling technology for many emerging applications. In th
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基于纹理语义特征的图像检索研究。关于图形图像检测的一篇论文。比较新，适合研究生读-Image retrieval based on texture semantic features. Detection of a graphic image on the paper. Relatively new for students to read
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the demand for automatically recognizing and retrieving medical image for screening,reference and management is growing faster than ever.In this paper present an intelligent content based image retrieval system called I-Browsewhich integrate both ico
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跨媒体检索新方法包括：CM、SM、SCM(This demo executes cross-modal retrieval experiments on
a novel dataset of Wikipedia pages.
Extract the zip file, open a matlab session and
run any of the example scritps:
- correlation matching 'demo_CM.m'
- semantic ma
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