Dynamic topology and relevance learning SOM-based algorithm for image clustering tasksImage clusteringSelf-organizationRelevance learningIn this paper, the task of unsupervised visual object categorization (UVOC) is addressed. We utilize a variant of Self-organizing Map (SOM) to cluster images in two ...
K-means is per- haps the most popular clustering algorithm and has been proven time and again to outperform state-of-the-art algorithms; however, because of its simplicity, it lacks the interpretability and visualization capabilities of the SOM. TADPole on the other hand, is a state-of-the-...
The generalization of the envSOM algorithm, a variant of Self-Organizing Map (SOM), is used to build an electrical model and visualize the information. The envSOM extended to n hierarchical phases allows us to obtain a more accurate model from real past data. The model is conditioned ...
Figure1summarizes the main ingredients of our SOM analysis pipeline. Details of the method and of the different analysis algorithms are provided in the Methods section below and, partly, in our previous publication [6]. In short: SOM is a neuronal network algorithm which transforms high-dimensiona...
Machine learning (ML) stands out as a potential strategy for upcoming mobile communication networks, encompassing 5G and beyond. Its potential lies in enhancing the effectiveness of intricate, diverse, and decentralized networks [8]. This paper introduces a self-optimization algorithm designed to ...
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its topological neighbors according to the current input vector so as to reveal the hidden statistical structures of the input space. However, the commonly used distance measure in the regular SOM algorithm is the Euclidean norm, thus the non-Euclidean ...
The generalization of the envSOM algorithm, a variant of Self-Organizing Map (SOM), is used to build an electrical model and visualize the information. The envSOM extended to n hierarchical phases allows us to obtain a more accurate model from real past data. The model is conditioned ...
The paper is organized as follows: in second chapter we mention classic SOM net- works and describe the basic variant we have used. In third chapter we describe our approach and provide the calculation algorithm, in fourth the GPU-based processing. The fifth chapter introduces experimental data ...
Patient data were also run through the Codified Genomics Pipeline (proprietary algorithm, Houston TX). The Exome Variant Server, 1000 Genomes, ExAc and ClinVar databases were checked on June 21, 2016. For the chromosomal microarray, genomic DNA was examined by array-based comparative genomic ...