【摘 要】
：
Graph data mining has been a crucial as well as inevitable area of research. Large amounts of graph data are produced in many areas, such as Bioinformatics, Cheminformatics, Social Networks, etc. Scal
【出 处】
：
Big Data Mining and Analytics
论文部分内容阅读
Graph data mining has been a crucial as well as inevitable area of research. Large amounts of graph data are produced in many areas, such as Bioinformatics, Cheminformatics, Social Networks, etc. Scalable graph data mining methods are getting increasin
其他文献
提出了一种基于代数迭代的Mojette变换层析重建算法。在确定最佳投影角度的基础上,结合传统层析技术中的乘性代数迭代算法进行重建。利用该算法对轴对称火焰进行了层析重建。数值模拟结果表明,与基于角的重建算法相比,该算法在噪声较大情况下的层析重建质量更好。
By improving the long-term correlation tracking(LCT) algorithm, an effective object tracking method, improved LCT(ILCT), is proposed to address the issue of occlusion. If the object is judged being oc
Generative adversarial networks(GANs) have become a competitive method among computer vision tasks. There have been many studies devoted to utilizing generative network to do generative tasks, such as
With the development of stereoscopic technology, more attention is attracted on the stereoscopic three-dimensional(S3 D) content and service, and researches on images and videos have emerged in large
设计了一种基于图像块细粒度的自适应单像素成像算法。首先获取目标的低分辨图像,将其分为四等块,根据每块中重要小波系数的个数与分布,将其分为非重要、重要和半重要三类。非重要块不采样;重要块全采样;半重要块进行迭代分块、分类,部分采样。利用小波反变换重建高分辨图并重复上述步骤,直到重建图像达到目标分辨率。实验结果表明,对于背景平滑的医学生物图像,本文方法能够在相同采样率下至少提高重建图像PSNR约2 d
针对图像中棒材识别问题,提出了一种新的标记分水岭的棒材分割识别方法,该方法结合距离变换与梯度重构对标记点进行限定,使用分水岭变换完成棒材识别。首先利用棒材图像低频部分进行阈值的自动提取,对区域对应的距离图中的局部极值点进行筛选。提取棒材图像中低频成份对应的局部极值区域,结合局部极值点得到前景标记。然后基于前景标记进行距离分水岭变换,将分水岭变换得到的脊线作为背景标记。最后对梯度重构以后的棒材图像基
Ghost imaging(GI) is thought of as a promising imaging method in many areas. However, the main drawback of GI is the huge measurement data and low signal-to-noise ratio. In this paper, we propose a no
A method of single-shot phase-shifting digital holography with a photon-sieve-filtering telescope is proposed. Three copy images with different phases are first generated by use of a monofocal photon-
因为相息图具有很好的衍射效率,所以经常被用在计算全息中。在计算相息图时,随机相位被加入到物体对象中从而扩散全息图中的物体光,但随机相位的添加会造成重建图像中产生相当大的散斑噪声。为了改善这一问题,本文首先针对随机相位的范围进行分析,研究了初始的随机相位对全息图成像质量的影响,再通过粒子群算法寻找最优的随机相位范围。在计算全息图时会存在部分信息的丢失,所以对全息图进行迭代运算能弥补全息图间的差异。故
One of the technical bottlenecks of traditional laser-induced breakdown spectroscopy(LIBS) is the difficulty in quantitative detection caused by the matrix effect. To troubleshoot this problem,this pa