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Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines
[article]
2019
arXiv
pre-print
Complex image processing and computer vision systems often consist of a processing pipeline of functional modules. We intend to replace parts or all of a target pipeline with deep neural networks to achieve benefits such as increased accuracy or reduced computational requirement. To acquire a large amount of labeled data necessary to train the deep neural network, we propose a workflow that leverages the target pipeline to create a significantly larger labeled training set automatically,
arXiv:1811.12108v2
fatcat:hbxww2u2szc7xeipfyzrv5zp3y