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分类效率 meaning in English

classification effectiveness

Examples

  1. Experimental results show that the recognition rate of the proposed classification strategy is higher than that of the single feature domain method , and the strategy is more efficient than the conventional structural neural network
    实验结果表明,动作分类准确率高于传统的单特徵集单分类器的分类方法,且训练、分类效率高于结构化神经网络特徵融合方法。
  2. We can prove from the result of experiment that the web text mining approach could be more efficient than other classification algorithms whatever in precision , recall rate , or in novelty of knowledge . moreover , the technology is language independence
    从实验结果看,基于粗糙集的web文本分类算法无论在分类精度、分类效率,还是知识的新颖程度方面,都比以往分类算法有明显提高;而且,这种技术是语言独立的。
  3. Compared with the other traditional algorithms , our synergetics based classification has the distinguished superiorities in feature extraction layer . the adjoint vectors representing the statistic feature of fingerprint images make global retrieve possible , promote the classification efficiency and deduce the feature extraction difficulty
    与传统特征提取过程不同,伴随向量提取了指纹像素域的统计特征,在指纹库中形成整体检索,有效提高了分类效率,降低了特征提取的难度。
  4. Interval frame classification is proposed . in this thought , features extract and classification are treated at interval frames instead of each frame , which debases time complexity of classification algorithm . and the methods of using temporal consistency and scene - dependent features are described
    提出隔帧分类的思想,将每帧都进行的特征提取与分类处理改为隔帧处理,降低了分类算法的时间复杂度,并描述了利用时间一致性约束和场景相关特征提高分类效率的方法。
  5. In order to improve the efficiency of classification based on feature matching , the method of azimuth estimation from sar image is studied . a method of target ' s azimuth estimation from sar image using peak featur e based on linear regression is proposed , besides goodish estimation accuracy and high computation efficiency , it can also provide the confidence interval of the estimation , which can meet the need of model - based sar atr system that uses feature very well
    为了提高基于特征匹配的saratr系统的分类效率,论文进一步研究了sar图像目标方位角估计方法,提出了一种利用峰值特征基于线性回归的sar目标方位角估计方法,该方法除了具有计算速度快、估计精度较高的特点之外,还能在估计方位角的同时,给出该估计的置信区间,从而能更好地满足利用特征基于模型saratr系统的需要。
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Related Words

  1. 提高效率
  2. 石灰效率
  3. 水泥效率
  4. 效率轨迹
  5. 效率管理
  6. 动态效率
  7. 排除效率
  8. 转轮效率
  9. 凝结效率
  10. 冷凝效率
  11. 分类向量
  12. 分类校对
  13. 分类协议 标界协议
  14. 分类械斗
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