The LSTM networks have high performance in solving the vanishing gradient problem that is observed in recurrent neural networks ... of the proposed state activation functions-based LSTM classifiers ...

In this paper, we design a few-shot Siamese Neural Networks combined with pre-trained models ... a comparatively small dataset and performs well for a five-class classification problem. We use the ...

Explore 20 essential activation functions implemented in Python for deep neural networks—including ELU, ReLU, Leaky ReLU, ...

Confused about activation functions in neural networks? This video breaks down what they are, why they matter, and the most common types — including ReLU, Sigmoid, Tanh, and more! #NeuralNetworks #Mac ...

Enzyme kinetic data from the BRENDA database were mapped onto the genome-scale metabolic model of Saccharomyces cerevisiae to ...

mobile digital devices used fMRI neuroimaging to identify specific brain activation differences during ... Writing by hand is associated with stronger neural encoding and memory retrieval.