Thus, we propose a non-negative model of the SPNN, to obtain better interpretability of the network learning. We restrict the values of the weights and biases ...
SPNN outperforms other pyramidal neural networks and presents a similar performance when compared to Convolutional Neural Network (CNN) and Sup- port Vector ...
The feature maps of ConvL correspond to convolution kernels of the same size, and they convolve with the feature maps from the previous layer [23] .
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LIPNet is a pyramidal neural network with lateral inhibition developed for pattern recognition ... image reconstruction in the same structure. For a given ...
This paper applies PyraNet to determine gender from a facial image, and compares its performance on the standard facial recognition technology (FERET) ...
Oct 2, 2023 · Non-negative structured pyramidal neural network for pattern recognition. In Proc. Intl. Joint Conf. on Neural Networks, pages. 1–7, 2018.
It is shown how constraining neurons' weights to be nonnegative improves the interpretability of a network's operation. People can understand complex ...
The Pyramidal Neural Networks (PNN) are an example of a successful recently proposed model inspired by the human visual system and deep learning theory.
Missing: negative | Show results with:negative
The first pyramidal layer is connected to the input image, and it is followed by one or more pyramidal layers. The last pyramidal layer is connected to 1-D.
Nov 15, 2020 · We develop a novel data-driven framework to extract white matter bundles and their associated grey matter networks from neonatal tractography data.
Missing: Recognition. | Show results with:Recognition.