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Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data

机译：判别性群集细化：在有限训练数据的情况下改进对象类别识别

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Liu Yang; Rong Jin; Caroline Pantofaru; Rahul Sukthankar;
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年度 2008
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1. Learning Discriminatively Reconstructed Source Data for Object Recognition With Few Examples [J] . Pai-Heng Hsiao, Feng-Ju Chang, Yen-Yu Lin IEEE Transactions on Image Processing . 2016,第8期

机译：学习区分重构源数据以识别对象的例子很少
2. Training data selection for improving discriminative training of acoustic models [J] . Berlin Chen, Shih-Hung Liu, Fang-Hui Chu Pattern recognition letters . 2009,第13期

机译：选择训练数据以改善声学模型的判别训练
3. Reusing training data with generative/discriminative hybrid model for practical acceleration-based activity recognition [J] . Quan Kong, Takuya Maekawa Computing . 2014,第9期

机译：利用生成/判别混合模型重用训练数据以进行基于加速的实际活动识别
4. Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data [C] . Liu Yang, Rong Jin, Pantofaru, Computer Vision and Pattern Recognition (CVPR), 2007 IEEE Conference on . 2007

机译：区分性聚类细化：在训练数据有限的情况下提高对象类别的识别能力
5. Object category data model: A new data model for object-oriented database management systems. [D] . Zygta, Adane H. 2000

机译：对象类别数据模型：面向对象的数据库管理系统的新数据模型。
6. The calibrated model-based concordance improved assessment of discriminative ability in patient clusters of limited sample size [O] . David van Klaveren, Ewout W. Steyerberg, Mithat Gönen, 2019

机译：校准的基于模型的一致性改进了有限样本量患者群中判别能力的评估
7. Unifying discriminative visual codebook generation with classifier training for object category recognition [O] . Yang, Liu, Jin, Rong, Sukthankar, Rahul, 2008

机译：通过分类器训练统一可区分的可视代码簿生成，以进行对象类别识别
8. Additional Remarks on Designing Category-Level Attributes for Discriminative Visual Recognition. [R] . Yu, F. X., Cao, L., Feris, R. S., 2013

机译：关于为判别性视觉识别设计类别级别属性的补充说明。

Discriminative Cluster Refinement: Improving Object Category Recognition Given Limited Training Data

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