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xdcode3
- 为了实现彩色栅格地图道路的全自动提取，提出了一种闭环反馈提取彩色 栅格地图道路的方法。在地图图像数学模型的基础上，根据地图中对象的颜色特征对地图图 像进行规范化处理。在采用一些算法去除噪声后提取道路，对道路进行细化处理。依据道路 和噪声的特征建立一些判据判断道路的正确性，把道路的提取变成了根据判据不断修正道路 的循环过程，实现道路的全自动提取。试验结果表明了该方法具有较高的准确性、全自动化 和通用性。-color raster to the road map automati
CBIR
- Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval, Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network,CONTENT BASED IMAGE RETRIEVAL,Relevance Feedback,A survey of browsing models for content based
06-005
- this is a paper on image encryption using cipher feedback mode
Simulation-visual-mechanism
- 提出一个小波域多尺度马尔柯夫随机场模型用于模拟视觉系统在图像分割中的若干功能。针对人类视觉系统具有特征检测器、等级层次性、双向连续性、学习机制等功能，对输入场景，该模型用小波变换提供该场景图像的稀疏表示，模拟特征检测器功能 用金字塔结构模拟等级层次性 用两类信息流模拟双向连接性，分别刻画自底向上的输入图像特征提取过程以及自顶向下的反馈过程 用迭代过程模拟学习机制 采用多尺度马尔柯夫随机场模型实现图像分割。-Put forward a wavelet domain multi-scale mark
Energy-Efficient-Cooperative-Image-Transmission-(
- We compare the energy efficiency of some transmission schemes in wireless sensor networks. By constraining the system to end-to-end throughput requirements, we assume that the nodes in multi-hop and cooperative schemes operate at a spectral e
CBIR
- 基于内容的图像检索 基于颜色、纹理、形状的图像检索 基于区域的图像检索 基于语义的图像检索 相关反馈 -Based on the content-based image retrieval based on color, texture, shape-based image retrieval region-based image retrieval based on semantic image retrieval relevance feedback
urlJAVAWEBAP
- 、程序简单，本程序仅一个类，你只需修改URL和替换图片就可以生成你的安卓应用 2、应用有6个菜单键，你可以自定义（有关于，反馈，刷新等功能） 3、webView使用了背景图片，防止加载时出现空白，同时也宣传应用品牌 4、应用支持友盟统计 5、程序开启缓存（当本地没有缓存时，从网上下载） 6、支持webview里上传文件 -, The procedure is simple, this program is only one class, you simply modify
Relevance-Feedback-
- 图像检索相关反馈方面牛人的文章。很有参考价值。-The paper about the relevance feedback of Image retrieval . it is very useful.
article
- Nowadays, Content-Based Image Retrieval (CBIR) is the mainstay of image retrieval systems. To understand the query semantics and users expectations so as to communicate faithful results in terms of accuracy, Relevance Feedback (RF) was incorp
derniere-version-maroc
- In the current decade, we are witnessing a great interest in Content Based Image Retrieval (CBIR) together with a wealth of promising technologies, paved for a large number of new mechanisms and systems. In terms of mechanisms, a strong trend towards