Abstract—As there are increasing needs of sharing data for machine learning, there is growing attention for the owners of the data to claim the ownership.
Project: DeepStamp. Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset. DeepStamp is a framework for visible-watermarking.
Visible watermarking has been an effective way to claim the ownership of visual data, yet the visibly watermarked images are not regarded as a primary source ...
On the Feasibility of Training Neural Networks with Visibly Watermarked ... • Minimize Accuracy Drops: a network trained with watermarked data.
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Sanghyun Hong, Tae-Hoon Kim, Tudor Dumitras, Jonghyun Choi: Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset.
Sanghyun Hong, Tae-Hoon Kim, Tudor Dumitras, Jonghyun Choi: Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset.
International Conference on Machine Learning (ICML). 2019. PDF | Code. Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset
Tae-hoon Kim's 4 research works with 48 citations, including: Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset.
Poster: On the Feasibility of Training Neural Networks with Visibly Watermarked Dataset. As there are increasing needs of sharing data for machine learning ...