ICLR (The International Conference on Learning Representations) is one of the most important international machine learning conferences. It’s popularity is growing fast, putting it on a par with such conferences as ICML, NeurIPS or CVPR.
Although machine learning is seen as a monolith, this cutting-edge technology is diversified, with various sub-types including machine learning, deep learning, and the state-of-the-art technology of deep reinforcement learning.
In the previous post we explained what region of interest pooling (RoI pooling for short) is. In this one, we present an example of applying RoI pooling in TensorFlow. We base it on our custom RoI pooling TensorFlow operation. We also use Neptune as a support in our experiment performance tracking.
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