Description: 对图像Gabor特征的提取，一个非常有效的特征,并用SVM对图像进行分类-get the gabor feature of a image,a very effective feature，and use SVM to classify the pictures Platform: |
Size: 16384 |
Author:soon |
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Description: Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM． - Abstract : As a powerful tool for image processing ，bi-dimensional empirical mode decomposition ( BEMD)
covers a wide range of applications． In this paper ，we explore a novel hyperspectral classification algorithm
which integrates BEMD and support vector machine ( SVM) ． By virtue of BEMD，the selected hyperspectral
bands are decomposed into several bi-dimensional intrinsic mode functions ( BIMFs) ，which reflect the essential
properties of hyperspectral image． We further make full use of SVM ，which is a supervised classification tool
widely accepted ，to classify the suitable sum of BIMFs． Experimental results indicate that though the proposed
method has no advantage in computing time ，it exhibits higher classification accuracy and stability than the clas-
sical SVM． Platform: |
Size: 356352 |
Author:刘国华 |
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Description: Cervical cancer is one of the deadliest cancers known and is also a key research area in image processing. The main problem with this cancer is that it cannot be detected as it doesn’t throw any symptoms until the final stages. This is attributed to the cancer itself and also to the lack of pathologists available to screen the cancer. Here we have proposed a novel approach to classify the various malignancies in cervical cyto images using the textural properties of the cervical cyto image. For grouping the stages of the cancer we have employed a decision based support system that would help classify the stages of the cancer and help the pathologist detect the cancer better. The proposed image has been tested with a set of images and has proved to be efficient. Platform: |
Size: 171008 |
Author:michael |
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Description: 使用SVM算法对CIFAR-10图片数据集进行分类，包括模型的训练，测试和参数的调优(Using SVM algorithm to classify CIFAR-10 image data sets, including model training, testing and parameter tuning) Platform: |
Size: 299008 |
Author:天地小成成 |
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Search - svm image classify