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

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 images into a latent space. Recently, Operational Neural Networks (ONNs) that learn the best non-linearity from a set o...

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Hauptverfasser:	Yılmaz, M. Akın, Keleş, Onur, Güven, Hilal, Tekalp, A. Murat, Malik, Junaid, Kıranyaz, Serkan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computer Vision and Pattern Recognition
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