Description: 压缩包里包含了如下关于目标检测的文献
1.一种基于背景减除与三帧差分的运动目标检测算法
2.Suboptimal Target Tracking in Clutter
3.A Study of a Target Tracking Algorithm Using Global Nearest Neighbor Approach
4.基于改进概率数据关联滤波的红外小运动目标跟踪
5.运动图像分析
6.Tracking of Humans Using Masked Histograms and Mean Shift-This zip file contains some papers and book about tracking Platform: |
Size: 10564608 |
Author:YIN HANGYU |
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Description: In this paper, we present two novel class-based
weighting methods for the Euclidean nearest neighbor algorithm
and compare them with global weighting methods
considering empirical results on a widely accepted time series
classification benchmark dataset. Our methods provide
higher accuracy than every global weighting in nearly half
of the cases and they have better overall performance. We
conclude that class-based weighting has great potential for
improving time series classification accuracy and it might be
extended to use with other distance functions than the Euclidean
distance. Platform: |
Size: 153600 |
Author:amijeet |
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Description: In this paper, we present two novel class-based
weighting methods for the Euclidean nearest neighbor algorithm
and compare them with global weighting methods
considering empirical results on a widely accepted time series
classification benchmark dataset. Our methods provide
higher accuracy than every global weighting in nearly half
of the cases and they have better overall performance. We
conclude that class-based weighting has great potential for
improving time series classification accuracy and it might be
extended to use with other distance functions than the Euclidean
distance. Platform: |
Size: 153600 |
Author:amijeet |
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Description: 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance
metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
learning conditions: supervised learning versus unsupervised learning, learning in a global sense versus in a local sense and the distance matrix based on linear kernel versus nonlinear kernel. In addition, this paper discusses a number of techniques
that is central to distance metric learning, including convex programming, positive semi-definite programming, kernel learning, dimension reduction, K Nearest Neighbor, large margin classification, and graph-based approaches. Platform: |
Size: 322560 |
Author:刘建飞 |
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Description: NW小世界网络的构成原则为：从一个环状的规则网络开始，网络含有N个结点，每个结点向与它最近邻的K个结点连出K条边，并满足N>>K>>In(N)>>1。随后进行随机化加边，以概率p在随机选取的一对节点之间加上一条边。其中，任意两个不同的节点之间至多只能有一条边，并且每一个节点都不能有边与自身相连。改变p值可以实现从最近邻耦合网络(p=0)向全局耦合网络(p=1)转变。在p足够小和N足够大时，NW小世界模型本质上等同于WS小世界模型。
-NW constitutive principles of small-world networks: from the rules of a ring network, network with N nodes, each node is connected to the K node with its nearest neighbor K edges, and meet N > > K > > In (N) > > 1. Followed by randomization into the plus side, with probability p with an edge between a pair of nodes in a randomly selected. Wherein between any two different nodes at most only one edge, and each node can not have a side connected with itself. P value can be changed to achieve the transition from the nearest neighbor coupling network (p = 0) coupled to the global network (p = 1). When p is small enough and large enough N, NW small-world model is essentially the same as the WS small-world model. Platform: |
Size: 2048 |
Author:freebank |
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Description: In the proposed algorithm, these two issues are solved by a novel predicate, which is defined by the sequential probability ratio test (SPRT) and the minimal cost criterion. Starting from an over-segmented image, neighboring regions are progressively merged if there is an evidence for merging according to this predicate. We show that the merging order follows the principle of dynamic programming. This formulates image segmentation as an inference problem, where the final segmentation is established based on the observed image. We also prove that the produced segmentation satisfies certain global properties. In addition, a faster algorithm is developed to accelerate the region merging process, which maintains a nearest neighbor graph (NNG) in each iteration. Platform: |
Size: 59392 |
Author:michael |
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Search - global nearest neighbor