Description: The Matlab functions and scripts in the MA toolbox are:
- ma_sone wav (PCM) to sone (specific loudness sensation)
- ma_mfcc wav (PCM) to MFCCs (Mel Frequency Cepstrum Coefficients)
- ma_sh sone to Spectrum Histogram
- ma_ph sone to Periodicity Histogram
- ma_fp sone to Fluctuation Pattern
- ma_fc frame based representation (MFCCs or sone) to cluster model (Frame Clustering)
- ma_cms cluster models to distance (Cluster Model Similarity)
- ma_kmeans kmeans clustering (used by \"ma_fc\")
- ma_cm_visu visualize a cluster model (as returned by \"ma_fc\")
- ma_simple_eval script for a simple evaluation of similarity measures
- ma_simple_iom script for a simple islands of music interface
-The Matlab functions and scripts in the MA t oolbox are : - ma_sone wav (PCM) to betamethasone ('s specific loudness ensation) - ma_mfcc wav (PCM) to MFCCs (Mel Freq uency diagnoses Coefficients) - ma_sh betamethasone to Sp ectrum Histogram - ma_ph betamethasone to Periodicity Hi stogram - ma_fp betamethasone to Fluctuation Pattern-ma _fc frame based representation (MFCCs or betamethasone) to cluster model (Frame Clustering) - ma_cms cl uster models to distance (Cluster Model Simila rity) - ma_kmeans kmeans clustering (used by "m a_fc ") - ma_cm_visu visualize a cluster model ( as returned by "ma_fc") - ma_simple_eval scrip not for a simple evaluation of similarity measure s-ma_simple_iom script for a simple islands of music interface Platform: |
Size: 24961 |
Author:mesu |
Hits:
Description: The Matlab functions and scripts in the MA toolbox are:
- ma_sone wav (PCM) to sone (specific loudness sensation)
- ma_mfcc wav (PCM) to MFCCs (Mel Frequency Cepstrum Coefficients)
- ma_sh sone to Spectrum Histogram
- ma_ph sone to Periodicity Histogram
- ma_fp sone to Fluctuation Pattern
- ma_fc frame based representation (MFCCs or sone) to cluster model (Frame Clustering)
- ma_cms cluster models to distance (Cluster Model Similarity)
- ma_kmeans kmeans clustering (used by "ma_fc")
- ma_cm_visu visualize a cluster model (as returned by "ma_fc")
- ma_simple_eval script for a simple evaluation of similarity measures
- ma_simple_iom script for a simple islands of music interface
-The Matlab functions and scripts in the MA t oolbox are :- ma_sone wav (PCM) to betamethasone ('s specific loudness ensation)- ma_mfcc wav (PCM) to MFCCs (Mel Freq uency diagnoses Coefficients)- ma_sh betamethasone to Sp ectrum Histogram- ma_ph betamethasone to Periodicity Hi stogram- ma_fp betamethasone to Fluctuation Pattern-ma _fc frame based representation (MFCCs or betamethasone) to cluster model (Frame Clustering)- ma_cms cl uster models to distance (Cluster Model Simila rity)- ma_kmeans kmeans clustering (used by "m a_fc ")- ma_cm_visu visualize a cluster model ( as returned by "ma_fc")- ma_simple_eval scrip not for a simple evaluation of similarity measure s-ma_simple_iom script for a simple islands of music interface Platform: |
Size: 24576 |
Author:mesu |
Hits:
Description: 自己编写的基于直方图的遗传聚类算法，用于图象分割。-prepared based on their genetic histogram clustering algorithm for image segmentation. Platform: |
Size: 5120 |
Author:张清华 |
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Description: 基于二维直方图的图像模糊聚类分割方法，内有算法的参考论文。-Two-dimensional histogram based on fuzzy clustering image segmentation algorithm, which algorithm has the reference papers. Platform: |
Size: 212992 |
Author:方方 |
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Description: 经典迭代直方图分离聚类算法，该聚类算法基于图像直方图，非常适合于多类目标分割，计算速度非常快-Classical iterative separation histogram clustering algorithm, the clustering algorithm based on image histogram, very suitable for many types of object segmentation, calculation of very fast Platform: |
Size: 1024 |
Author:刘炎 |
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Description: In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
-In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
Platform: |
Size: 2048 |
Author:pramod |
Hits:
Search - histogram based clustering matlab