"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"..."视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。展开更多
Visualization methods for single documents are either too simple, considering word frequency only, or depend on syntactic and semantic information bases to be more useful. This paper presents an intermediary approach,...Visualization methods for single documents are either too simple, considering word frequency only, or depend on syntactic and semantic information bases to be more useful. This paper presents an intermediary approach, based on H. P. Luhn’s automatic abstract creation algorithm, and intends to aggregate more information to document visualization than word counting methods do without the need of external sources. The method takes pairs of relevant words and computes the linkage force between them. Relevant words become vertices and links become edges in the resulting graph.展开更多
提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的...提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的倒排索引,用于视频片段的匹配和检索。这种方法保留了局部特征的显著性及其相对位置关系,而且有效地压缩了视频的表达,加速的视频的匹配和检索过程。实验结果表明,和已有方法相比,基于"bag of words"的视频匹配方法在大视频样本库上获得了更高的检索精度和检索速度。展开更多
使用Visual Basic编程,采用正则表达式批量提取由Web of Science导出的Bib Tex题录中所有Keywords字段关键词,按需合并所得关键词的同义词、近义词及词形变化词,然后将出现频度的统计数据写入Excel表,并编制Excel宏自动生成折线图,实现...使用Visual Basic编程,采用正则表达式批量提取由Web of Science导出的Bib Tex题录中所有Keywords字段关键词,按需合并所得关键词的同义词、近义词及词形变化词,然后将出现频度的统计数据写入Excel表,并编制Excel宏自动生成折线图,实现关键词分布的简单可视化。情报工作者后续可借助Excel功能对该程序生成的Excel表执行复杂的数据组合分析,以提高工作效率。展开更多
Bag of Words算法是一种有效的基于语义特征提取与表达的物体识别算法,算法充分学习文本检索算法的优点,将图片整理为一系列视觉词汇的集合,提取物体的语义特征,实现感兴趣物体的有效检测与识别。文章主要研究了Bagof Words算法的框架...Bag of Words算法是一种有效的基于语义特征提取与表达的物体识别算法,算法充分学习文本检索算法的优点,将图片整理为一系列视觉词汇的集合,提取物体的语义特征,实现感兴趣物体的有效检测与识别。文章主要研究了Bagof Words算法的框架和基本内容。展开更多
Objective: To analyze clinical psychological nursing research hotspots in China and variation trends in order to provide reference points on the current state of development of clinical psychological nursing and futur...Objective: To analyze clinical psychological nursing research hotspots in China and variation trends in order to provide reference points on the current state of development of clinical psychological nursing and future research hotspots.Method: Clinical psychological nursing research literature sourced from Wanfang Data for the three periods of 2007-2009, 2010-2012, and 2013-2015 were selected as the research sample. A bibliographic co-occurrence analysis system(BICOMB software) was used to perform keyword word frequency analysis and generate a keyword co-occurrence matrix. In addition, Ucinet software's Netdraw tool was used to create visualized network diagrams.Results: A total of 27890 articles were retrieved, and word frequency analysis revealed that the highestfrequency keywords consisted of anxiety, depression, the elderly, expectant women, coronary heart disease, diabetes, breast cancer, perioperative period, quality of life, and psychological intervention.Research hotspot analysis revealed that consistent hotspots comprised anxiety, depression, health education, and perioperative period; expectant women became a hotspot during 2010-2012, and quality of life and efficacy became hotspots during 2013-2015.Conclusions: In addition to the care process, clinical psychological nursing research hotspots in China have increasingly included the effectiveness of psychological nursing and impact on patient quality of life. In addition, research hotspots have been influenced by the incidence of illnesses and people's health consciousness.展开更多
BACKGROUND： The role of the left midfusiform gyrus as a target for visual word processing has been a topic of discussion. Numerous studies have utilized alphabetic writing for subject matter. However, few have addres...BACKGROUND： The role of the left midfusiform gyrus as a target for visual word processing has been a topic of discussion. Numerous studies have utilized alphabetic writing for subject matter. However, few have addressed visual processing of Chinese characters in the left midfusiform gyrus. OBJECTIVE： To verify visual processing of Chinese characters and images in the left midfusiform gyrus using functional magnetic resonance imaging. DESIGN, TIME AND SETTING： A blocked design paradigm study. Experiments were performed at the Room of Magnetic Resonance, Guangdong Provincial Second People＇s Hospital, China from May to June 2009. PARTICIPANTS： A total of eight undergraduate students were recruited from Guangzhou University of China, comprising two females and six males, aged 20-23 years. The subjects were right-handed which was determined by a Chinese standard questionnaire. None of the subjects had a history of psychoneurosis, familial disease, color blindness, or color weakness. METHODS： A total of eight undergraduates were enrolled as subjects. Picture-naming and verb generation tasks were employed through the use of functional magnetic resonance imaging. Analysis of Functional Neurolmages software was used to process the data. MAIN OUTCOME MEASURES： Visual processing of Chinese characters and images in the left midfusiform gyrus was measured. RESULTS： Picture-naming and verb generation tasks were shown to significantly activate the bilateral midfusiform gyrus. Activation occurred in the visual word form area of the left midfusiform gyrus. CONCLUSION： The left midfusiform gyrus plays a general role in visual processing of Chinese characters and images.展开更多
文摘"视觉词袋"(Bag of Visual Words,BOV)算法是一种有效的基于语义特征表达的物体识别算法。针对传统BOV模型存在的不足,综合利用SAR图像的灰度和纹理特征,提出基于感兴趣目标(Target of Interest,TOI)的"视觉词袋"算法。首先,对训练图像进行TOI选取,用灰度共生矩阵模型提取TOI的纹理特征,再结合灰度特征,组成多维特征向量集,以簇内相似度最高、数据分布密度最大为准则,生成"视觉词袋"。其次,对测试图像,依据已生成的"视觉词袋",采用支持向量机(Support Vector Machine,SVM)分类器,实现SAR图像感兴趣目标的有效分类。实验结果表明,与传统的"视觉词袋"构建算法相比,该算法在分类正确率提高的同时,能够在训练图像较少的情况下达到良好的分类效果。
文摘Visualization methods for single documents are either too simple, considering word frequency only, or depend on syntactic and semantic information bases to be more useful. This paper presents an intermediary approach, based on H. P. Luhn’s automatic abstract creation algorithm, and intends to aggregate more information to document visualization than word counting methods do without the need of external sources. The method takes pairs of relevant words and computes the linkage force between them. Relevant words become vertices and links become edges in the resulting graph.
文摘提出了一种利用"bag of words"模型对视频内容进行建模和匹配的方法。通过量化视频帧的局部特征构建视觉关键词(visual words)辞典,将视频的子镜头表示成若干视觉关键词的集合。在此基础上构建基于子镜头的视觉关键词词组的倒排索引,用于视频片段的匹配和检索。这种方法保留了局部特征的显著性及其相对位置关系,而且有效地压缩了视频的表达,加速的视频的匹配和检索过程。实验结果表明,和已有方法相比,基于"bag of words"的视频匹配方法在大视频样本库上获得了更高的检索精度和检索速度。
文摘使用Visual Basic编程,采用正则表达式批量提取由Web of Science导出的Bib Tex题录中所有Keywords字段关键词,按需合并所得关键词的同义词、近义词及词形变化词,然后将出现频度的统计数据写入Excel表,并编制Excel宏自动生成折线图,实现关键词分布的简单可视化。情报工作者后续可借助Excel功能对该程序生成的Excel表执行复杂的数据组合分析,以提高工作效率。
基金supported by a scientific research project of Shanxi Provincial Health Department,China(No.201201031)
文摘Objective: To analyze clinical psychological nursing research hotspots in China and variation trends in order to provide reference points on the current state of development of clinical psychological nursing and future research hotspots.Method: Clinical psychological nursing research literature sourced from Wanfang Data for the three periods of 2007-2009, 2010-2012, and 2013-2015 were selected as the research sample. A bibliographic co-occurrence analysis system(BICOMB software) was used to perform keyword word frequency analysis and generate a keyword co-occurrence matrix. In addition, Ucinet software's Netdraw tool was used to create visualized network diagrams.Results: A total of 27890 articles were retrieved, and word frequency analysis revealed that the highestfrequency keywords consisted of anxiety, depression, the elderly, expectant women, coronary heart disease, diabetes, breast cancer, perioperative period, quality of life, and psychological intervention.Research hotspot analysis revealed that consistent hotspots comprised anxiety, depression, health education, and perioperative period; expectant women became a hotspot during 2010-2012, and quality of life and efficacy became hotspots during 2013-2015.Conclusions: In addition to the care process, clinical psychological nursing research hotspots in China have increasingly included the effectiveness of psychological nursing and impact on patient quality of life. In addition, research hotspots have been influenced by the incidence of illnesses and people's health consciousness.
基金the Key Programming Research Project of Education Science During the 11~(th) Five-Year Plan Period of Guangdong Province, No. 06TJZ014the Programming Project of Education Science During the 11~(th) Five-Year Plan Period of Guangzhou City, No. 07B290
文摘BACKGROUND： The role of the left midfusiform gyrus as a target for visual word processing has been a topic of discussion. Numerous studies have utilized alphabetic writing for subject matter. However, few have addressed visual processing of Chinese characters in the left midfusiform gyrus. OBJECTIVE： To verify visual processing of Chinese characters and images in the left midfusiform gyrus using functional magnetic resonance imaging. DESIGN, TIME AND SETTING： A blocked design paradigm study. Experiments were performed at the Room of Magnetic Resonance, Guangdong Provincial Second People＇s Hospital, China from May to June 2009. PARTICIPANTS： A total of eight undergraduate students were recruited from Guangzhou University of China, comprising two females and six males, aged 20-23 years. The subjects were right-handed which was determined by a Chinese standard questionnaire. None of the subjects had a history of psychoneurosis, familial disease, color blindness, or color weakness. METHODS： A total of eight undergraduates were enrolled as subjects. Picture-naming and verb generation tasks were employed through the use of functional magnetic resonance imaging. Analysis of Functional Neurolmages software was used to process the data. MAIN OUTCOME MEASURES： Visual processing of Chinese characters and images in the left midfusiform gyrus was measured. RESULTS： Picture-naming and verb generation tasks were shown to significantly activate the bilateral midfusiform gyrus. Activation occurred in the visual word form area of the left midfusiform gyrus. CONCLUSION： The left midfusiform gyrus plays a general role in visual processing of Chinese characters and images.
