Procedural Learning With Robust Visual Features via Low Rank Prior

Procedural Learning With Robust Visual Features via Low Rank Prior

In order to apply a convolutional neural network (CNN) to unseen datasets, a common way is to train a CNN using a pre-trained model on a big dataset by fine-tuning it instead of starting from scratch. How to control the fine-tuning progress to get the desired properties is still a challenging proble...

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Bibliographic Details
Main Authors: Haifeng Li, Li Chen, Hailun Ding, Qi Li, Bingyu Sun, Guohua Wu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Low-rank approximation
procedural learning
knowledge transfer
robustness visual feature
sparse
Online Access:https://ieeexplore.ieee.org/document/8624510/

Internet

https://ieeexplore.ieee.org/document/8624510/

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