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[Graph programdiblook_SPMG

Description: Split and merge Algorithm for Image Processing . It uses a quad tree as data structure, which is created at running time using breath first method, and a stopping criterion . The stoping criterion method can be changed , i just used to the difference of means of the regions which should be merged , compared with some threshold.
Platform: | Size: 1433600 | Author: TOAMNA_AMARA | Hits:

[matlabfsmem_mvgm

Description: Free Split and Merge Expectation-Maximization algorithm for Multivariate Gaussian Mixtures. This algorithm is suitable to estimate mixture parameters and the number of conpounds-Free Split and Merge Expectation-Maximization algorithm for Multivariate Gaussian Mixtures. This algorithm is suitable to estimate mixture parameters and the number of conpounds
Platform: | Size: 220160 | Author: ewizlab | Hits:

[Graph programsplitmerge

Description: SPLITMERGE Segment an image using a split-and-merge algorithm.
Platform: | Size: 2048 | Author: Wagner | Hits:

[Special Effectsweimianfenge

Description: 一种改进的图象分割程序,分割出来效果相当好,尤其对于丰富的图象,保证别人没有上传过-Based on graph cut image segmentation algorithm, split the result was very good, especially for texture-rich images, ensure that no one else uploaded
Platform: | Size: 2048 | Author: | Hits:

[Othersplitmerge

Description: SPLITMERGE Segment an image using a split-and-merge algorithm. G = SPLITMERGE(F, MINDIM, @PREDICATE) segments image F by using a split-and-merge approach based on quadtree decomposition. MINDIM (a positive integer power of 2) specifies the minimum dimension of the quadtree regions (subimages) allowed. If necessary, the program pads the input image with zeros to the nearest square size that is an integer power of 2. This guarantees that the algorithm used in the quadtree decomposition will be able to split the image down to blocks of size 1-by-1. The result is cropped back to the original size of the input image. In the output, G, each connected region is labeled with a different integer. - SPLITMERGE Segment an image using a split-and-merge algorithm. G = SPLITMERGE(F, MINDIM, @PREDICATE) segments image F by using a split-and-merge approach based on quadtree decomposition. MINDIM (a positive integer power of 2) specifies the minimum dimension of the quadtree regions (subimages) allowed. If necessary, the program pads the input image with zeros to the nearest square size that is an integer power of 2. This guarantees that the algorithm used in the quadtree decomposition will be able to split the image down to blocks of size 1-by-1. The result is cropped back to the original size of the input image. In the output, G, each connected region is labeled with a different integer.
Platform: | Size: 2048 | Author: dilir | Hits:

[Graph RecognizeISODATA

Description: ISODATA算法是一种基于统计模式识别的,非常经典的非监督学习动态聚类算法,有较强的实用性。ISODATA算法不仅可以通过调整样本所属类别完成样本的聚类分析,而且可以自动地进行类别的“合并”和“分裂”,从而得到类数比较合理的聚类结果。-ISODATA algorithm is based on statistical pattern recognition, unsupervised learning is the classic dynamic clustering algorithm, there is a strong practical. ISODATA algorithm can be completed by adjusting the sample of category clustering analysis of samples, and the categories can be automatically " merge" and " split" to get class numbers more reasonable clustering results.
Platform: | Size: 186368 | Author: wcb | Hits:

[MPIquicksort

Description: This code is an MPI version of the sorting algorithm QuickSort in c++. The partitioning step is meda sequantially, but the split and merge steps are made using Send and Recieve methods.
Platform: | Size: 2048 | Author: saretaxd | Hits:

[Othermulti-object-tracking

Description: globally optimal solution to multi-object tracking with merged measuements 里面还有一篇发表于ICCV上的文章,另外还有一个配套的PPT,但没找到代码,文章中对多目标跟踪运用了贪心算法,并且详细分析了merge,split,occlusion情况-globally optimal solution to multi-object tracking with merged measuements there is also an article published in ICCV on, plus a supporting PPT, but did not find the code, the article on the use of multi-target tracking greedy algorithm, and detailed analysis of the merge, split, occlusion situation
Platform: | Size: 3729408 | Author: rita | Hits:

[Mathimatics-Numerical algorithmssplitmerge

Description: This is a split and merge type of segmentation algorithm
Platform: | Size: 3072 | Author: Mary | Hits:

[Graph programsplitmerge

Description: SPLITMERGE Segment an image using a split-and-merge algorithm.
Platform: | Size: 2048 | Author: 电子测量 | Hits:

[Graph program2134

Description: 基于区域的分裂与合并的算法 能够对图像进行简单的分裂与合并-The image can be split and merge based on a simple split and merge algorithm region
Platform: | Size: 1024 | Author: 朱达 | Hits:

[Graph programother

Description: 区域生长与合并的算法。能够简单地对图像进行区域分裂与合并-Region growing and merging algorithm. The image can be easily split and merge area
Platform: | Size: 34816 | Author: 朱达 | Hits:

[Othersplit-and-merge

Description: segments image F by using a split-and-merge approach based on quadtree decomposition. MINDIM (a positive integer power of 2) specifies the minimum dimension of the quadtree regions (subimages) allowed. If necessary, the program pads the input image with zeros to the nearest square size that is an integer power of 2. This guarantees that the algorithm used in the quadtree decomposition will be able to split the image down to blocks of size 1-by-1. The result is cropped back to the original size of the input image.-segments image F by using a split-and-merge approach based on quadtree decomposition. MINDIM (a positive integer power of 2) specifies the minimum dimension of the quadtree regions (subimages) allowed. If necessary, the program pads the input image with zeros to the nearest square size that is an integer power of 2. This guarantees that the algorithm used in the quadtree decomposition will be able to split the image down to blocks of size 1-by-1. The result is cropped back to the original size of the input image.
Platform: | Size: 2048 | Author: Narayana Reddy | Hits:

[Software EngineeringAction-Detection

Description: This paper advances prior work by proposing a joint learning framework to simultaneously identify the spatial and temporal extents of the action of interest in training videos. To get pixel-level localization results, our method uses dense trajectories extracted videos as local features to represent actions. We first present a trajectory split-and-merge algorithm to segment a video into the background and several separated foreground moving objects. In this algorithm, the inherent temporal smoothness of human actions is exploited to facilitate segmentation. Then, with the latent SVM framework on segmentation results, spatial and temporal extents of the action of interest are treated as latent variables that are inferred simultaneously with action recognition. Experiments on two challenging datasets show that action detection with our learned spatial and temporal extents is superior than state-of-the-art methods.
Platform: | Size: 4917248 | Author: robin | Hits:

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