9 citations · 34 across the 7 of their papers we have counts for
4 papers · 1 filter
Compressing Weight-updates for Image Artifacts Removal Neural Networks
Yat Hong Lam, Alireza Zare, Caglar Aytekin +4
In this paper, we present a novel approach for fine-tuning a decoder-side neural network in the context of image compression, such that the weight-updates are better compressible.…
Compressibility Loss for Neural Network Weights
Caglar Aytekin, Francesco Cricri, Emre Aksu
In this paper we apply a compressibility loss that enables learning highly compressible neural network weights. The loss was previously proposed as a measure of negated sparsity of…
Block-optimized Variable Bit Rate Neural Image Compression
Caglar Aytekin, Xingyang Ni, Francesco Cricri +3
In this work, we propose an end-to-end block-based auto-encoder system for image compression. We introduce novel contributions to neural-network based image compression, mainly in…
A Theoretical Investigation of Graph Degree as an Unsupervised Normality Measure
Caglar Aytekin, Francesco Cricri, Lixin Fan +1
For a graph representation of a dataset, a straightforward normality measure for a sample can be its graph degree. Considering a weighted graph, degree of a sample is the sum of th…