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In this paper we assess the economic viability of innovation by producers relative to two increasingly important alternative models: innovations by single user individuals or firms, and open collabora...
Annotation errors can significantly hurt classifier performance, yet datasets are only growing noisier with the increased use of Amazon Mechanical Turk and techniques like distant supervision that aut...
The mean-shift algorithm is a popular algorithm in computer vision and image processing. It can also be cast as a minimum gamma-divergence estimation. In this paper we focus on the "blurring" mean shi...
The classical shift retrieval problem considers two signals in vector form that are related by a cyclic shift. In this paper, we develop a compressive variant where the measurement of the signals is u...
针对传统模糊C均值(FCM) 聚类算法对结构复杂图像分割效果不理想且算法执行效率较低的缺陷, 提出一种融合均值平移(mean shift) 的FCM聚类算法. 利用mean shift 算法将图像分成若干同质区域, 将此区域视为新的节点; 通过图像局部信息熵描述新节点的空间和灰度特征; 采用能较好模拟人眼非线性视觉响应的指数函数进行相似性测度. 实验结果表明, 对于复杂背景图像和含噪声图像, 所提...
特征空间分析是视觉跟踪中的关键问题. 针对mean shift 跟踪算法中模板匹配问题, 提出了特征贡献度概念, 有效减少了背景和噪声因素干扰, 使重要性特征在匹配中起到关键作用; 利用结构二值分布图携带空间结构信息的优点, 很好地避免了统计特征的匹配误差, 在一定程度上提高了跟踪的精度和鲁棒性. 仿真实验结果表明该算法具有一定的优越性和实时性, 在跟踪目标存在变形、噪声、遮挡时也可以达到比较理想...
传统的mean-shift 跟踪算法不能跟踪目标的旋转、缩放运动, 且常常因此造成定位不准. 鉴于此, 将尺度不变特征变换(SIFT) 特征检测融入到mean-shift 跟踪过程, 提出SIFT 特征点的尺度变化与目标的尺度变化成正比, 特征点主方向变化与目标旋转角度一致, 给出了基于SIFT 特征的自适应目标尺度、方向计算方法, 且利用带方向、可变带宽的椭圆核改进传统的mean-shift 跟...
Abstract: Investigates the theme known as "Knowledge Management" (KM) in three large Brazilian organizations trying to discuss its concepts, constituent elements, managerial approaches and tools, whi...
One of the main objectives of educators is to identify inspiring and interactive approaches to learning, and to encourage students to be more receptive and co-operative in the classroom. To help educa...
Shift-share analysis of employment as a measuring instrument for human resource management is proposed by this study. The results obtained through this technique can assist human resource management o...
Australia’s Prime Minister, Mr Kevin Rudd, may possibly have read The New Asian Hemisphere and been encouraged by its grand visionary register—“The time to restructure the world order has come. We sho...
将基于DESO的运动预测算法和Mean Shift算法相结合,形成一种新的基于Mean Shift的快速目标跟踪算法.该算法以DESO预测位置作为Mean Shift算法下一帧候选模型的计算中心,实现了对快速运动目标的跟踪,并通过DESO对目标运动轨迹进行预测,较好地解决了目标完全遮挡时的跟踪问题.实验结果表明,该算法具有预测精度高,实时性好,抗遮挡能力强的优点.

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