semantic gap造句
例句与造句
- the uml 2.0 specification clarifies some of the critical semantic gaps in the original version
:uml2.0规范澄清了一些在老版本中的严重语义缺陷。 - however, there has a big hurdle in content-based image retrieval till the present moment, i . e ., “ semantic gap ”
但是基于内容的图像检索遇到了一个棘手的问题,即“语义鸿沟”。 - the idea of an object dbms ( odbms ) is to store the objects as such, and thus bridge the semantic gap all the way to the database
对象数据库管理就是将对象储存然后建立提取数据的路径.这样,我们要查找某个数据就不必间接而又缓慢地寻找了 - in order to narrow the semantic gap existing in content-based image retrieval ( cbir ), a novel retrieval technology called auto-extended multi query examples ( amqe ) is proposed
摘要为了缩短基于内容图像检索存在的“语义鸿沟”，提出了一种自动扩展的多示例查询技术。 - in this thesis, we research on the bridging “ semantic gap ” and extracting the semantic feature, and then we propose two effective algorithms to extract the semantic feature
本文在解决“语义鸿沟”,提取语义特征方面作了一系列比较深入地研究,并提出了两种有效的解决模型。 - It's difficult to find semantic gap in a sentence. 用semantic gap造句挺难的
- in this paper, a lot research work has been done around three points : how to abstract and index low-level feature of images, how to retrieval images in semantic level, and how to fill the semantic gap by relevant feedback technique
前者研究的是根据自动获取的图像低层特征，从图像数据库中检索出相关图像；而后者研究的是如何从多种渠道获取图像语义信息，并根据语义检索相关图像。 - however, this technology still faces much difficulty to bridge the semantic gap between image semantic features and the lower features, resulting in the fact that the extracted content features still mainly centered upon the lower features such as color, texture and shape
然而,由于图像语义特征和低层特征的“鸿沟”问题,给图像检索技术带来了很大困难,目前提取的内容特征仍集中于颜色、纹理、形状等低层特征。 - “ semantic gap ” is the gulf between the low-level image visual feature and high-level concepts, the images can be different of semantic concept while having similar visual feature, and they can also be different of visual feature while having the same concept
“语义鸿沟”是指图像的低级视觉特征和高级语义特征之间的差距,由计算机计算出来的低级特征的相关性很难说明图像在语义层上的相似性,语义层上的相似性也无法证明低级特征的相关性。 - relevance feedback techniques are important approaches closing up the semantic gap between high-level concepts and low-level features in image retrieval effectively, and efficient indexing schemes for high-dimensional data are required for real-time retrieval in large-scale image database
相关反馈方法是弥合图像检索中高层语义和低层特征之间语义间隔的一个重要途径，而有效的高维索引机制则是面向大规模图像库的检索能够达到实时性要求的关键技术。 - considering an enormous semantic gap problem between the low-level visual features and high-level semantic information of images, and the fact that the accuracy of content-based image classification and retrieval depends greatly on the description of low-level visual features, an image semantic classification approach is proposed based on multiple-hyperplanes support vector machines ( mhsvms )
摘要由于图像的低层可视特征与高层语义内容之间存在巨大的语义鸿沟，而基于内容的图像分类和检索准确性极大依赖低层可视特征的描述，本文提出了一种基于多超平面支持向量机的图像语义分类方法。