… approach” using Spiking Neural Networks (SNNs). The … Neural Network (CNN) with the
same topology for approximating the best accuracy we can expect from the feature extraction…

… self-organizing neural networks this is only the possibility of learning without a teacher, but
just not the internal state of knowledge … knowledge contained in the data can be extracted with …

… for features extraction using a Multi-view self-organizing maps… model called self-organizing
incremental neural network (… retrieval framework based on nonlinear features extraction, …

… approach for feature extraction based on deep Self-Organizing Map (SOM) network, named
… widespread and widely used unsupervised learning-based neural networks. Image features …

… to extract deep features from raw data, which responds to the first question. Second, an efficient
selforganizing … Specifically, IDPT is used to extract effective features from complex data. …

… method of ship radiated noise with K-nearest neighbor mutual information variational … ),
neural network estimation time entropy (NNetEn) and self-organizing map (SOM) neural network …

… The core of patent infringement detection is information retrieval. A good information retrieval
capability is critical to the stakeholders of the patent. Faced with a large number of patent …

… the tuning of the parameters of the extracted fuzzy rules in [54]. … these issues, a self-organizing
fuzzy neural network with an … First, a self-organizing mechanism, based on both neuronal …

… prediction method using a self-organizing neural network (SOM) to identify and predict
tight-sand gas reservoirs in areas with few or no wells. First, we extracted seismic attributes data …

… information chain of the marine, backward marine information resources and isolation of …
data mining technology, the marine data extraction, preprocessing, classification, clustering, …