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L*ReLU: Piece-wise Linear Activation Functions for Deep Fine-grained Visual Categorization
We demonstrate our approach for the task of Fine-grained Visual Categorization (FGVC), running experiments on seven different benchmark datasets.
The Quest for the Golden Activation Function
To avoid the manual design or selection of activation functions, we build on the idea of genetic algorithms to learn the best activation function for a given task.
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