… The objective is to adapt the parameters of the self-organizing map, represented by the …
Image features extraction is a major goal for many computer vision and pattern recognition …

… based on nonlinear features extraction, using a hierarchical self-organizing map HSOM. A …
of the field of self-organizing systems for data analysis, relate to the self-organizing maps core …

… In this work, we want to use AEs as feature extractors with unsupervised learning. In such
cases, the feature map representation of a Convolutional AE (CAE) is most of the time of a …

… to the implementation of DeepCluster [20], we separate learning feature extractor and feature
… In addition, we also intend to apply the proposed methods on other computer vision tasks, …

… for image representation is a major goal for many computer vision and pattern recognition …
the performance of proposed DCSOM feature extraction method by changing the most …

… face processing schemes that composed the contemporary intelligent vision-based … and
implementation of a human facial recognition system based on PCA as a feature extractor (facial …

… One of such challenges is poor underwater vision resulting … echo images on a frontal vision
since acoustic signals can pass … An optical camera was employed in [2] for visual feedback …

… In this paper, inspired by Self-Organizing Map (Kohonen, … Learning classifier, the Deep
Self-organizing Cube, (DSOC) … across class spaces while implementing multi-output learning, …

… -ups in wide-field optical surveys. The identification of … self-organizing map (DESOM)
to this ‘real-bogus’ classification problem. DESOM combines an autoencoder and a self-organizing …

… of the OPTICS method … feature extraction was the normalization procedure, which naturally,
did not affected their lengths, and consequently, the final lengths of our vectors of features, in …