models and enormous training datasets, GPUs have become increasingly necessary to train neural networks. This is largely because conventional optimization algorithms rely on stochastic gradient ...
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training a keypoint detector to only find those points that are suitable to the needs of the given task. We demonstrate our approach in an urban environment, where the keypoint detector should focus ...
Adversarial Training (AT), a dynamic regularization technique, can resist the worst-case perturbations on input features and is a promising choice to improve model robustness and generalization....
modeling techniques, training deep learning model on GPU becomes a popular choice. However, due to the inherent complexity of deep learning models and the limited memory resources on modern GPUs, ...
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