Publications associées à Dictionary Compression in Point Cloud Data Management

Publications associées (34)

Fiducial-cosmology-dependent systematics for the DESI 2024 BAO analysis

Jiaxi Yu, Antoine Philippe Jacques Rocher

When measuring the Baryon Acoustic Oscillations (BAO) scale from galaxy surveys, one typically assumes a fiducial cosmology when converting redshift measurements into comoving distances and also when defining input parameters for the reconstruction algorit ...

IOP Publishing Ltd2025

A Human-Centric Approach to Explainable AI for Personalized Education

Vinitra Swamy

Deep neural networks form the backbone of artificial intelligence (AI) research, with potential to transform the human experience in areas ranging from autonomous driving to personal assistants, healthcare to education. However, their integration into the ...

EPFL2025

PixelsDB: Serverless and NL-Aided Data Analytics with Flexible Service Levels and Prices

Anastasia Ailamaki

Serverless query processing has become increasingly popular due to its advantages, including automated resource management, high elasticity, and pay-as-you-go pricing. For users who are not system experts, serverless query processing greatly reduces the co ...

2024

Sequential CNN-based Enhancement of Ultrafast Ultrasound Imaging for Sparse Arrays

Jean-Philippe Thiran, Roser Vinals Terres

With the emergence of ultra-portable ultrasound systems, the need to reduce cost and complexity of ultrasound systems has intensified. Sparse arrays, employing fewer transducer elements to acquire images, offer a viable solution by effectively minimizing d ...

European Signal Processing Conference, EUSIPCO2024

Event Data Stream Compression Based on Point Cloud Representation

Touradj Ebrahimi, Bowen Huang

The Dynamic Vision System (DVS) is a novel image acquisition system that works only when there is a brightness change in a pixel, resulting in a stream of events including timestamps, spatial coordinates and the sign of the bright- ness change (increase or ...

2023

Evaluating the effect of sparse convolutions on point cloud compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

2023

Communication-efficient distributed training of machine learning models

Thijs Vogels

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

EPFL2023

Towards JPEG AIC part 3: visual quality assessment of high to visually lossless image coding

Touradj Ebrahimi, Michela Testolina, Evgeniy Upenik

Due to the increasing number of pictures captured and stored every day by and on digital devices, lossy image compression has become inevitable to limit the needed storage requirement. As a consequence, these compression methods might introduce some visual ...

SPIE2022

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

Volume change response and fabric evolution of granular MX80 bentonite along different hydro-mechanical stress paths

Alessio Ferrari, Jose Antonio Bosch Llufriu, Patrycja Ewelina Baryla

Despite the increasing understanding of bentonite behaviour, there is still missing evidence on how different hydro-mechanical loadings, including sequences of hydration and compression, affect the fabric and the volume change behaviour of the material. It ...

Springer Nature2022

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

FEM of stress partition during compression of WC-10 wt.% Co with realistic 3D morphology

Daniele Mari, Lucas Eric Jacques Degeneve

A Finite Element Model is developed to represent the mechanical behavior of WC-10 wt.% Co in compression tests. In this research, realistic three-dimensional model is obtained by slicing a sample by Focused Ion Beam and reconstituting it, resulting in two ...

ELSEVIER SCI LTD2022

Increasing the Energy Efficiency of Gas Boosters for Hydrogen Storage and for Refueling Stations

Alfred Rufer

A new electrically driven gas booster is described as an alternative to the classical air-driven gas boosters known for their poor energetic efficiency. These boosters are used in small scale Hydrogen storage facilities and in refueling stations for Hydrog ...

MDPI2023

Stochastic distributed learning with gradient quantization and double-variance reduction

Sebastian Urban Stich

We consider distributed optimization over several devices, each sending incremental model updates to a central server. This setting is considered, for instance, in federated learning. Various schemes have been designed to compress the model updates in orde ...

TAYLOR & FRANCIS LTD2022

Structured and tiled-based pruning of Deep Learning models targeting FPGA implementations

Alexandre Schmid

Model compression techniques have lead to a reduction of size and number of computations of Deep Learning models. However, techniques such as pruning mostly lack of a real co-optimization with hardware platforms. For instance, implementing unstructured pru ...

IEEE2022

Efficient Concurrent Analytical Query Processing using Data and Workload-conscious Sharing

Panagiotis Sioulas

Analytical workloads are evolving as the number of users surges and applications that submit queries in batches become popular. However, traditional analytical databases that optimize-then-execute each query individually struggle to provide timely response ...

EPFL2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Anne-Claire Marie Billault--Roux, Gionata Ghiggi

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Reshaping Perception for Autonomous Driving with Semantic Keypoints

Lorenzo Bertoni

The field of artificial intelligence is set to fuel the future of mobility by driving forward the transition from advanced driver-assist systems to fully autonomous vehicles (AV). Yet the current technology, backed by cutting-edge deep learning techniques, ...

EPFL2022

A Framework for Autonomic Computing for In Situ Imageomics

Nina Marion Aurélia Van Tiel

In situ imageomics is a new approach to study ecological, biological and evolutionary systems wherein large image and video data sets are captured in the wild and machine learning methods are used to infer biological traits of individual organisms, animal ...

The Institute of Electrical and Electronics Engineers, Inc2023