In this paper, a nonlinear classification network model based on predefined evenly-distributed class centroids (PEDCC) is proposed. Its analytical solution can ...

Sep 19, 2024 · In this paper, a nonlinear classification network model based on predefined evenly-distributed class centroids (PEDCC) is proposed. Its ...

Through predefined evenly-distributed class centroids, CSAE proposed in this paper maps training labels to these class centers and can use latent variables to ...

This paper presents an image clustering algorithm based on predefined evenly-distributed class centroids (PEDCC) and composite cosine distance.

May 31, 2021 · Predefined evenly-distributed class centroids (PEDCC) can be widely used in models and algorithms of pattern classification, ...

In this paper, a nonlinear classification network model based on predefined evenly-distributed class centroids (PEDCC) is proposed. Its analytical solution can ...

A PEDCC-based loss function based on the concept of predefined evenly-distributed class centroids (PEDCC) in CSAE network is proposed, which can make the ...

PEDCC-FC is a linear layer with fixed parameters (the fixed parameters are C center points), which is used to calculate the cosine distance between the feature ...

Cite Email Print Share. Analytical learning classifier based on predefined evenly-distributed class centroids. Authors: Hu, Haiping | Huo, Wei | Yan, Yingying ...

Sep 10, 2024 · In this paper, a new autoencoder model - classification supervised autoencoder (CSAE) based on predefined evenly-distributed class centroids ( ...