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Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories

机译：从几个训练样例中学习生成视觉模型：在101个对象类别上测试增量贝叶斯方法

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Li Fei-fei;
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年度 2004
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1. Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories [J] . Li Fei-Fei, Rob Fergus, Pietro Perona Computer vision and image understanding . 2007,第1期

机译：从几个训练示例中学习生成的视觉模型：在101个对象类别上测试的增量贝叶斯方法
2. Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots [J] . Akira Taniguchi, Tadahiro Taniguchi, Angelo Cangelosi Frontiers in Neurorobotics . 2017,第2016期

机译：利用贝叶斯生成模型进行跨情境学习的多模式类别和机器人单词学习
3. Incrementally Learning Objects by Touch: Online Discriminative and Generative Models for Tactile-Based Recognition [J] . Soh H., Demiris Y. Haptics, IEEE Transactions on . 2014,第4期

机译：通过触摸增量学习对象：基于触觉的识别的在线判别和生成模型
4. Learning Generative Visual Models from Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories [C] . LI FEI-FEI, PIETRO PERONA, ROB FERGUS SME Technical Conference . 2004

机译：从次数训练中学习生成视觉模型：在101个对象类别中测试了一个增量贝叶斯方法
5. Zero Shot Learning for Visual Object Recognition with Generative Models [D] . Vyas, Maunil. 2020

机译：用生成模型进行视觉对象识别的零射击学习
6. Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots [O] . Akira Taniguchi, Tadahiro Taniguchi, Angelo Cangelosi 2017

机译：利用贝叶斯生成模型进行跨情境学习的多模式类别和机器人单词学习
7. Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots [O] . Akira Taniguchi, Tadahiro Taniguchi, Angelo Cangelosi 2017

机译：基于贝叶斯生成模型的机器人多模态分类与单词学习的跨情境学习

Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories

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