33 citations · 68 across the 7 of their papers we have counts for
7 papers
Unlocking Layer-wise Relevance Propagation for Autoencoders
Kenyu Kobayashi, Renata Khasanova, Arno Schneuwly +2
Autoencoders are a powerful and versatile tool often used for various problems such as anomaly detection, image processing and machine translation. However, their reconstructions a…
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…
Isometric Transformation Invariant Graph-based Deep Neural Network
Renata Khasanova, Pascal Frossard
Learning transformation invariant representations of visual data is an important problem in computer vision. Deep convolutional networks have demonstrated remarkable results for im…
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…
Graph-Based Classification of Omnidirectional Images
Renata Khasanova, Pascal Frossard
Omnidirectional cameras are widely used in such areas as robotics and virtual reality as they provide a wide field of view. Their images are often processed with classical methods,…
Graph-based Isometry Invariant Representation Learning
Renata Khasanova, Pascal Frossard
Learning transformation invariant representations of visual data is an important problem in computer vision. Deep convolutional networks have demonstrated remarkable results for im…
Multi-modal image retrieval with random walk on multi-layer graphs
Renata Khasanova, Xiaowen Dong, Pascal Frossard
The analysis of large collections of image data is still a challenging problem due to the difficulty of capturing the true concepts in visual data. The similarity between images co…