Dendritic Artificial Neural Networks Outperform Traditional Models in Accuracy, Robustness, and Efficiency

Dendritic artificial neural networks (dANNs) that incorporate structured connectivity and restricted input sampling outperform traditional artificial neural networks (ANNs) in image classification tasks, achieving higher accuracy, greater robustness, and higher efficiency with significantly fewer trainable parameters.