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- To boost the recognition performance in this one training sample application scenario, we extract context information as another cue for recognizing people. 为了在这单一训练样本的情况下提高人脸分类的识别性能，我们亦由输入的照片集中，萃取出前后文讯息，来做为分类判断的另一种线索。
- Face recognition with one training sample by repeatedly used face features 复用特征组合的单幅人脸图像识别
- There's only one train into town per hour. 去城里的电车一小时只有一趟。
- Just as one train departs, another comes into view. 一列火车刚刚离开,另外一列就进入了视野。
- Singapore only has one train station. 新加坡只有一座火车站?
- There is only one train to Paris today. 今天只有一列去巴黎的列车。
- Wavelet-based Training Sample Enhancement for Face Recognition with One Training Sample 基于小波的训练样本增强的单样本人脸识别
- One trained in the description and cataloging of printed matter. 目录学家训练对印刷品的目录和内容作整理的人
- The method divides theoriginal data into two parts in term of "close" degree between the original sample and forecast sample: one is initial sample, the other is training sample. 本方法对原有的样品数据根据与待预测样品的关系的“密切”程度分为两个部分,一部分是初始样品,一部分是训练样品。
- A horse that trots, especially one trained for harness racing. 小跑步的马尤指为拖车赛马而训练的小跑马
- One train leaves Los Angeles at15 mph heading for New York. 一列火车以每小时15英里的速度离开洛杉矶，朝纽约进发。
- one training sample 单训练样本
- One trained in teaching; a teacher. 教师受过教育训练的人; 教师
- Yes,I mean whether it is necessary for me to change from one train to another. 外宾: 是的，我是说是否有必要从某次车换到另外一次车上去?
- To classify the collectivity, uaually a training sample is needed.The classification and statistical indexes of the training sample are known. 为了对总体分类，一般应该有训练样本，它的分类和统计指标都是已知的。
- Yes, I mean whether it is necessary for me to change from one train to another. 外宾: 是的，我是说是否有必要从某次车换到另外一次车上去?
- An automatic text categorization mechanism based on CBR was presented,the training sample library was converted to the case library and the document was classified by KNN. 文中提出了一种基于CBR的文本自动分类方法,先用聚类方法把训练样本库转换为范例库,然后用KNN思想分类。
- A horse that trots,especially one trained for harness racing. 小跑步的马尤指为拖车赛马而训练的小跑马
- The denominator of generally neural network output often tends to be zero,leading to infinite loop when training sample data.The reliability of results is debased. 常规神经网络在当训练样本时分母项易趋于0,导致运算进入死循环,降低了结果的可信度。
- For a multifactor power load prediction problem and typical training sample selection, a new method for Short-Term Load Forecasting (STLF) based on data mining is put forward. 针对电力负荷受到多因素的影响以及典型训练样本选择问题,提出了一种基于数据挖掘技术的新型短期负荷预测方法。
