• Computer Science
• Published in ICIAP 2019
• DOI:10.1007/978-3-030-30642-7_29

Hebbian Learning Meets Deep Convolutional Neural Networks

@inproceedings{Amato2019HebbianLM,
  title={Hebbian Learning Meets Deep Convolutional Neural Networks},
  author={Giuseppe Amato and Fabio Carrara and Fabrizio Falchi and Claudio Gennaro and Gabriele Lagani},
  booktitle={ICIAP},
  year={2019}
}

• Giuseppe Amato, Fabio Carrara, +2 authors Gabriele Lagani

Neural networks are said to be biologically inspired since they mimic the behavior of real neurons. However, several processes in state-of-the-art neural networks, including Deep Convolutional Neural Networks (DCNN), are far from the ones found in animal brains. One relevant difference is the training process. In state-of-the-art artificial neural networks, the training process is based on backpropagation and Stochastic Gradient Descent (SGD) optimization. However, studies in neuroscience… CONTINUE READING

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