… 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 …

… ), is a type of computer vision application. It searches for an … in both phases, features
extraction and classification give … some feature extraction such as Ant algorithms, self-organizing …

… 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 …

… 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, …

… 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 …

… 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 …

… This is done via a learning technique called the self-organizing feature map (Kohonen
map). We evaluated our approach on 300 images with different sizes and fonts for handwritten …

… -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 …