most citedSelf-Organized Variational Autoencoders (Self-VAE) for Learned Image Compression

2 citations · 2 across the 2 of their papers we have counts for

collaborators
Showing eess.IVShow all

2 papers · 1 filter

eess.IV2024

PAON: A New Neuron Model using Padé Approximants

Onur Keleş, A. Murat Tekalp

Convolutional neural networks (CNN) are built upon the classical McCulloch-Pitts neuron model, which is essentially a linear model, where the nonlinearity is provided by a separate…

eess.IV2021★ 2 cited

Self-Organized Variational Autoencoders (Self-VAE) for Learned Image Compression

M. Akın Yılmaz, Onur Keleş, Hilal Güven +3

In end-to-end optimized learned image compression, it is standard practice to use a convolutional variational autoencoder with generalized divisive normalization (GDN) to transform…