3 accepted papers
Mixup provides interpolated training samples and allows the model to obtain smoother decision boundaries for better generalization. The idea can be naturally applied to the domain adaptation task, where we can mix the source and target samples to obtain domain-mixed samples for better adaptation. Ho…
The common paradigm of CNN-based action recognition modelsis to simply use the average of the dense predictions from every frame. However, these dense predictions are inefficient since all frames are evenly utilized regardless of the existence of the action. In real-time action recognition applicati
Accurate and fast inventory management algorithms are essential in the modern distribution industry. However, the configuration process of inventory management algorithms is very expensive, and the direct comprehensive management of inventory procedures is labor intensive and inaccurate. Therefore,…