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Publications associées (32)

Towards learning-based image compression for storage on DNA support

The demand for data storage has grown exponentially over the past decades. Current archival solutions have significant shortcomings, such as high resource requirements and a lack of sufficient longevity. In contrast, research on DNA-based storage has been ...

2023

On Block Prediction For Learning-Based Point Cloud Compression

Touradj Ebrahimi, Evangelos Alexiou

Point clouds are among popular visual representations for immersive media. However, the vast amount of information generated during their acquisition requires effective compression for practical applications. Although relevant activities from standardizati ...

IEEE2021

Towards neural network approaches for point cloud compression

Touradj Ebrahimi, Evangelos Alexiou, Kuan Tung

Point cloud imaging has emerged as an efficient and popular solution to represent immersive visual information. However, the large volume of data generated in the acquisition process reveals the need of efficient compression solutions in order to store and ...

2020

A new end-to-end image compression system based on convolutional neural networks

Touradj Ebrahimi, Pinar Akyazi

In this paper, two new end-to-end image compression architectures based on convolutional neural networks are presented. The proposed networks employ 2D wavelet decomposition as a preprocessing step before training and extract features for compression from ...

2019

Perceptual Quality Study On Deep Learning Based Image Compression

Touradj Ebrahimi, Pinar Akyazi

Recently deep learning based image compression has made rapid advances with promising results based on objective quality metrics. However, a rigorous subjective quality evaluation on such compression schemes have rarely been reported. This paper aims at pe ...

IEEE2019

On the relevance of quality score metadata in genomic sequence data for omics applications

Ana Angelica Hernandez Lopez

High-throughput sequencing of DNA molecules has revolutionized biomedical research by enabling the quantitative analysis of the genome to study its function, structure and dynamics. It is driving sequencing-based experiments in life sciences as evidenced b ...

EPFL2019

Generalized dissipation dilution in strained mechanical resonators

Tobias Kippenberg, Dalziel Joseph Wilson, Nils Johan Engelsen, Sergey Fedorov, Ryan Daniel Schilling, Amir Hossein Ghadimi

Mechanical resonators with high quality factors are widely used in precision experiments, ranging from gravitational wave detection and force sensing to quantum optomechanics. Beams and membranes are well known to exhibit flexural modes with enhanced quali ...

AMER PHYSICAL SOC2019

Learning-Based Image Compression using Convolutional Autoencoder and Wavelet Decomposition

Touradj Ebrahimi, Pinar Akyazi

In this paper, a learning-based image compression method that employs wavelet decomposition as a preprocessing step is presented. The proposed convolutional autoencoder is trained end-to-end to yield a target bitrate smaller than 0.15 bits per pixel across ...

2019

Dynamic Adaptive Streaming for Multi-Viewpoint Omnidirectional Videos

Pascal Frossard, Francesca De Simone, Xavier Corbillon

Full immersion inside a Virtual Reality (VR) scene requires six Degrees of Freedom (6DoF) applications where the user is allowed to perform translational and rotational movements within the virtual space. The implementation of 6DoF applications is however ...

ASSOC COMPUTING MACHINERY2018

Caching of Bivariate Gaussians with Non-Uniform Preference Probabilities

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Caching is technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. We study this method in a lossy source coding setting with Gaussian databases. A good caching strategy minimizes the data ...

2017

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