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彩色图像边缘检测及分类,pdf格式的论文,详尽具体,硕士学位论文-Color image edge detection and classification, pdf format, paper, detailed concrete, a master' s degree thesis
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图像分类算法,2012年CVPR中的文章,效果还可以,采用“Local Naive Bayes Nearest Neighbor”方法-Image classification algorithm, CVPR 2012 article, the effect can also " Local Naive Bayes Nearest Neighbor method
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此文档包含对卷积神经网络的描述及在图像处理中的应用,对学习卷积神经网络有重要帮助。-The work presented here
uses image classifi cation performance (accurate discrimination between common
classes of objects) as a basis for comparing visual system models, and algorithms
for fi
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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 s
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texture based image analysis
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Abstract—Noninvasive ultrasound imaging of carotid plaques
allows for the development of plaque-image analysis methods associated
with the risk of stroke. This paper presents several plaqueimage
analysis methods that have been developed over th
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classification d image avec l algo FCM
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高分辨率遥感影像的支持张量机分类方法,此方法能够利用少量的训练样本实现更优的分类精度。-Support tensor machines resolution remote sensing image classification method, and this method can use a small amount of training samples to achieve better classification accuracy.
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讲述了图像的一种新颖的空间信息描述指标,对图像分类提取等有很大用处,特别是对高分辨率图像。-The novel tells the story of an image of the spatial information descr iptors for image classification extraction have great usefulness, especially for high-resolution images.
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object tracking and detection in video image processing. classification of objects in video.
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object tracking and detection in video image processing. classification of objects in video.
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object tracking and detection in video image processing. classification of objects in video.
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object tracking and detection in video image processing. classification of objects in video.
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object tracking and detection in video image processing. classification of objects in video.
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基于商空间粒度计算的SAR图像分类方法研究-SAR Image Classification Based on Granularity Computing of
Quotient Space Theory
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Hyperspectral image classification with limited
number of labeled pixels is a challenging task. In this paper, we
propose a bilayer graph-based learning framework to address
this problem. For graph-based classification, how to establish
the n
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Retinal exudates detection by dividing an image into regions and classification of exudates
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