This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, pos...This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, position’s priority and the association for a label with its feature. By establishing the scoring system, a formalized four-factors quality evaluation model is constructed. Last, this paper introduces the experimental result of the quality evaluation model applied to the automatic map labeling system-MapLabel.展开更多
相位展开是磁共振成像技术应用中最关键的环节之一,可以为磁共振的某些重要临床应用提供精确的相位信息。然而,由于临床磁共振成像过程中,部分区域真实的相位存在急剧变化,同时伴有不同性态的噪声污染,导致相位展开时存在信息的高度不...相位展开是磁共振成像技术应用中最关键的环节之一,可以为磁共振的某些重要临床应用提供精确的相位信息。然而,由于临床磁共振成像过程中,部分区域真实的相位存在急剧变化,同时伴有不同性态的噪声污染,导致相位展开时存在信息的高度不一致性。为了有效地解决上述难题,基于马尔可夫-最大后验(Markov Random Field& Maximum A Posterioi,MRF-MAP)模型,首次将相位展开看作计算机视觉中的标记问题,并结合磁共振相位数据的特点,设计出相位图的模糊质量图,完成相位展开的能量函数构建。针对能量函数的优化求解,采用高效的图割算法进行。展开更多
This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interl...This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interleaved Coded Modulation with Iterative Decoding (BICM-ID). The basic idea was to use the so called (1,7) constellation (which is a capacitive efficient constellation) instead of the conventional 8-PSK constellation and to choose the most suitable mapping for it. A comparative study between the combinations most suitable mapping/(1,7) constellation and SSP mapping/conventional 8-PSK constellation has been carried out. Simulation results showed that the 1st combination significantly outperforms the 2nd combination and with only 4 iterations, it gives better performance than the 2nd combination with 8 iterations. A gain of 4 dB is given by iteration 4 of the 1st combination compared to iteration 8 of the 2nd combination at a BER level equal to 10-5, and it (iteration 4 of the 1st combination) can attain a BER equal to 10-7 for, only, a SNR = 5.6 dB.展开更多
The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only...The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only with robot's vision.By imitating spatial cognizing mechanism of human,the robot constantly received the information of artificial labels at cognitive-guide points in a wide range of structured environment to achieve the perception of the environment and robot navigation.The immune network algorithm was used to form the environmental awareness mechanism with "distributed representation".The color recognition and SIFT feature matching algorithm were fused to achieve the memory and cognition of scenario tag.Then the cognition-guide-action based cognizing semantic map was built.Along with the continuously abundant map,the robot did no longer need to rely on the artificial label,and it could plan path and navigate freely.Experimental results show that the artificial label designed in this work can improve the cognitive ability of the robot,navigate the robot in the case of semi-unknown environment,and build the cognizing semantic map favorably.展开更多
关系抽取作为知识图谱等诸多领域的上游任务,具有广泛应用价值,近年来受到广泛关注。关系抽取模型普遍存在暴露偏差问题,抽取文本普遍存在实体嵌套和实体重叠问题,这些问题严重影响了模型性能。因此,提出了一种基于片段标注的实体关系...关系抽取作为知识图谱等诸多领域的上游任务,具有广泛应用价值,近年来受到广泛关注。关系抽取模型普遍存在暴露偏差问题,抽取文本普遍存在实体嵌套和实体重叠问题,这些问题严重影响了模型性能。因此,提出了一种基于片段标注的实体关系联合抽取模型(span-labeling based model,SLM),主要包括:将实体关系抽取问题转化为片段标注问题;使用滑动窗口和三种映射策略将词元(token)序列进行组合排列重新平铺成片段(span)序列;使用LSTM和多头自注意力机制进行片段深层语义特征提取;设计了实体关系标签,使用多层标注方法进行关系标签分类。在英文数据集NYT、WebNLG上进行实验,相对于基线模型F1值显著提高,验证了模型的有效性,能有效解决上述问题。展开更多
针对基于标记编码的加密图像可逆数据隐藏存在图像冗余未充分利用和信息泄露问题,提出一种基于MSB(Most Significant Bit)二维标记的加密图像可逆数据隐藏(Reversible Data Hiding in Encrypted Image,RDH-EI)算法.为提高算法的嵌入容量...针对基于标记编码的加密图像可逆数据隐藏存在图像冗余未充分利用和信息泄露问题,提出一种基于MSB(Most Significant Bit)二维标记的加密图像可逆数据隐藏(Reversible Data Hiding in Encrypted Image,RDH-EI)算法.为提高算法的嵌入容量,在二维标记图生成阶段,根据原始与预测像素值构造出差异序列,生成MSB二维标记(l1,l2).第一维l1和第二维l2分别记录原始与预测像素值初始连续相同MSBs位数和后继连续相反MSBs(Subsequent Consecutive Opposite MSBs,SCO-MSBs)位数.SCO-MSBs的使用提高像素冗余的利用率,结合范式哈夫曼编码实现嵌入容量的提升.为提高算法的安全性,在伪标记图与加密图像构造阶段,将二维标记图生成的编码流与保存所有辅助信息的额外数据流进行有效信息合并生成原始流后加密,同时在构造加密图像过程中生成用于标识可嵌入位置的伪标记图.原始流加密能有效防止图像信息泄露,伪标记图则用于确定嵌入的预留空间位置.实验结果表明,与现有同类算法相比,本文算法能防止标记图泄露并抵抗唯密文攻击,嵌入容量提高0.208 bpp以上,且算法实现完全可逆的同时,运行时间将近现有算法的1/4.展开更多
基金Funded by the National Natural Science Foundation of China (N0.40001019).
文摘This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, position’s priority and the association for a label with its feature. By establishing the scoring system, a formalized four-factors quality evaluation model is constructed. Last, this paper introduces the experimental result of the quality evaluation model applied to the automatic map labeling system-MapLabel.
文摘相位展开是磁共振成像技术应用中最关键的环节之一,可以为磁共振的某些重要临床应用提供精确的相位信息。然而,由于临床磁共振成像过程中,部分区域真实的相位存在急剧变化,同时伴有不同性态的噪声污染,导致相位展开时存在信息的高度不一致性。为了有效地解决上述难题,基于马尔可夫-最大后验(Markov Random Field& Maximum A Posterioi,MRF-MAP)模型,首次将相位展开看作计算机视觉中的标记问题,并结合磁共振相位数据的特点,设计出相位图的模糊质量图,完成相位展开的能量函数构建。针对能量函数的优化求解,采用高效的图割算法进行。
文摘This contribution proposes a new combination symbol mapper/8-ary constellation, which is a joint optimization of an 8-ary signal constellation and its symbol mapping operation, to improve the performance of Bit Interleaved Coded Modulation with Iterative Decoding (BICM-ID). The basic idea was to use the so called (1,7) constellation (which is a capacitive efficient constellation) instead of the conventional 8-PSK constellation and to choose the most suitable mapping for it. A comparative study between the combinations most suitable mapping/(1,7) constellation and SSP mapping/conventional 8-PSK constellation has been carried out. Simulation results showed that the 1st combination significantly outperforms the 2nd combination and with only 4 iterations, it gives better performance than the 2nd combination with 8 iterations. A gain of 4 dB is given by iteration 4 of the 1st combination compared to iteration 8 of the 2nd combination at a BER level equal to 10-5, and it (iteration 4 of the 1st combination) can attain a BER equal to 10-7 for, only, a SNR = 5.6 dB.
基金Projects(61203330,61104009,61075092)supported by the National Natural Science Foundation of ChinaProject(2013M540546)supported by China Postdoctoral Science Foundation+2 种基金Projects(ZR2012FM031,ZR2011FM011,ZR2010FM007)supported by Shandong Provincal Nature Science Foundation,ChinaProjects(2011JC017,2012TS078)supported by Independent Innovation Foundation of Shandong University,ChinaProject(201203058)supported by Shandong Provincal Postdoctoral Innovation Foundation,China
文摘The quick response code based artificial labels are applied to provide semantic concepts and relations of surroundings that permit the understanding of complexity and limitations of semantic recognition and scene only with robot's vision.By imitating spatial cognizing mechanism of human,the robot constantly received the information of artificial labels at cognitive-guide points in a wide range of structured environment to achieve the perception of the environment and robot navigation.The immune network algorithm was used to form the environmental awareness mechanism with "distributed representation".The color recognition and SIFT feature matching algorithm were fused to achieve the memory and cognition of scenario tag.Then the cognition-guide-action based cognizing semantic map was built.Along with the continuously abundant map,the robot did no longer need to rely on the artificial label,and it could plan path and navigate freely.Experimental results show that the artificial label designed in this work can improve the cognitive ability of the robot,navigate the robot in the case of semi-unknown environment,and build the cognizing semantic map favorably.
文摘关系抽取作为知识图谱等诸多领域的上游任务,具有广泛应用价值,近年来受到广泛关注。关系抽取模型普遍存在暴露偏差问题,抽取文本普遍存在实体嵌套和实体重叠问题,这些问题严重影响了模型性能。因此,提出了一种基于片段标注的实体关系联合抽取模型(span-labeling based model,SLM),主要包括:将实体关系抽取问题转化为片段标注问题;使用滑动窗口和三种映射策略将词元(token)序列进行组合排列重新平铺成片段(span)序列;使用LSTM和多头自注意力机制进行片段深层语义特征提取;设计了实体关系标签,使用多层标注方法进行关系标签分类。在英文数据集NYT、WebNLG上进行实验,相对于基线模型F1值显著提高,验证了模型的有效性,能有效解决上述问题。
