activity
20172020
most citedGuetzli: Perceptually Guided JPEG Encoder

26 citations · 29 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG20202 cited

Intelligent Matrix Exponentiation

Thomas Fischbacher, Iulia M. Comsa, Krzysztof Potempa +3

We present a novel machine learning architecture that uses the exponential of a single input-dependent matrix as its only nonlinearity. The mathematical simplicity of this architec…

eess.IV2019

Committee Draft of JPEG XL Image Coding System

Alexander Rhatushnyak, Jan Wassenberg, Jon Sneyers +15

JPEG XL is a practical approach focused on scalable web distribution and efficient compression of high-quality images. It provides various benefits compared to existing image forma…

cs.NE2019

Temporal Coding in Spiking Neural Networks with Alpha Synaptic Function: Learning with Backpropagation

Iulia M. Comsa, Krzysztof Potempa, Luca Versari +3

The timing of individual neuronal spikes is essential for biological brains to make fast responses to sensory stimuli. However, conventional artificial neural networks lack the int…

cs.CR2018

Randen - fast backtracking-resistant random generator with AES+Feistel+Reverie

Jan Wassenberg, Robert Obryk, Jyrki Alakuijala +1

Algorithms that rely on a pseudorandom number generator often lose their performance guarantees when adversaries can predict the behavior of the generator. To protect non-cryptogra…

cs.CV2018

Noise generation for compression algorithms

Renata Khasanova, Jan Wassenberg, Jyrki Alakuijala

In various Computer Vision and Signal Processing applications, noise is typically perceived as a drawback of the image capturing system that ought to be removed. We, on the other h…

cs.CV201726 cited

Guetzli: Perceptually Guided JPEG Encoder

Jyrki Alakuijala, Robert Obryk, Ostap Stoliarchuk +3

Guetzli is a new JPEG encoder that aims to produce visually indistinguishable images at a lower bit-rate than other common JPEG encoders. It optimizes both the JPEG global quantiza…