| 1. | Unit weight approach for model sediment
模型试验的泥沙重度浅析 |
| 2. | Novel weight approach for interval numbers comparison matrix in the analytic hierarchy process
中判断矩阵的区间权重及其一致性检验 |
| 3. | Sci . , 1996 , 2 : 637 - 649 . 15 salton g , buckley c . term - weighting approaches in automatic retrieval
Clascn方法可以和其他任何精确top - k算法相结合形成一个新的高效近似top - k算法。 |
| 4. | After simulating the two classic algorithms proposed by rui and aksoy , we propose a novel feature re - weighting approach for relevance feedback
在此基础上,提出了一种新的基于修改特征权重的相关反馈新算法。 |
| 5. | This resulted in the emergence of a broad consensus on a weighted approach to the measurement of risk , on and off the balance sheet
也就是说，达成交易所依据的条款，同两个独立主体在平等条件下所达成的交易依据的条款是同样的。 |
| 6. | On the basis of studying feature re - weighting approach for relevance feedback in cbir , we propose the algorithm of combining the lower - feature and semantic to retrieve images
本文在研究基于修改特征权重的相关反馈算法基础上,提出了综合低层特征和语义特征进行图像检索的算法。 |
| 7. | In this dissertation , we analyze the content - based image retrieval technology and several algorithms of the relevance feedback in cbir . our emphasis is the feature re - weighting approach for relevance feedback in cbir
本文全面分析了图像检索各种技术和图像检索技术中的相关反馈算法,对基于修改特征权重的相关反馈算法进行了重点分析,对经典算法进行了仿真实验。 |
| 8. | Exemplified with a number of representative systems which are highly valuable in industry and academically important , including electrode membranes of fuel cells , sesame seeds as well as hard bones and cartilages of marine fish , the extensive applications of microscopic mri images with various weighting approaches to the investigations of micro - structures and dynamics including the developmental processes of plants are demonstrated
以具有高度产业价值及重要学术意义的几个典型体系：燃料电池电极月莫、芝麻种子和海生鱼骨为例，说明各类加权图象在微结构和动态（包括植物生长过程）研究中的广泛应用。 |
| 9. | When taking part in the bci competition iii , t - weighted approach for feature extraction and reinforcement learning of classifier design are proposed . compared to other methods , t - weight approach has the advantages of requiring less a prior knowledge , exploring more information and computing faster . reinforcement learning is an optimization method both model driven and data driven aiming at mining the discriminative information as more as possible , and improving both the fitting and generalization ability of an existing classifier
相比其它特征提取方法, t加权方法具有对先验知识要求少、信息利用充分、计算快速等优点;而分类器设计的强化学习方法是模型驱动与数据驱动相结合的一种分类器优化方法,其思想在于充分挖掘样本判别信息,在已有分类器基础上进一步提高对数据的拟合能力及泛化能力。 |
