… [27] developed a single layer of a deep SOM network and a fully connected neural network
(… In general, the performance of deep neural networks (DNNs) is quite reliant on the avail…

… be extracted through appropriate organisation and summarisation. The self-organizing map
(SOM) is an artificial neural network … options have on the extracted information is developed, …

… single layer neural network, it is difficult to extract the feature … network (DBN) is an
energy-based deep neural network that … compared to basic deep neural networks. Thus, the first …

… network as complex features, our model encodes hierarchical feature representations
essentially different than artificial neural networks (… This project should include the extraction of …

… based on the self-organizing neural network have been done. For … examined several
self-organizing neural network-based … The SOM network is then run on the initial clusters to extract …

… based on neural networks where each neuron is related to … three neural networks based
on SOM (self-organizing maps) [… of samples allows extracting sufficient information for the …

… a probabilistic account for this neural network model. … extracted from the SOM. This is a
possible way of exploiting symbolic knowledge in combination with the knowledge extracted from …

… ] using Self-Organizing Maps (SOM). On the one hand, transfer learning is used to exploit a
Deep Neural Network (… Our first step consists in extracting relevant features from these inputs. …

… The use of self-organizing maps and artificial neural networks … extracting damage
indices from the ambient vibration response of a structure. The algorithm is based on self-organizing …

… , hindering their application in conventional artificial neural networks (ANNs). Here, a SR-…
Moreover, an unsupervised self-organizing map (SOM) neural network is first developed for …