Publications associées à Multi-scale approaches

SVGC-AVA: 360-Degree Video Saliency Prediction With Spherical Vector-Based Graph Convolution and Audio-Visual Attention

Pascal Frossard, Chenglin Li, Li Wei, Qin Yang, Yuelei Li

Viewers of 360-degree videos are provided with both visual modality to characterize their surrounding views and audio modality to indicate the sound direction. Though both modalities are important for saliency prediction, little work has been done by joint ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Influence of pore-scale heterogeneity on the precipitation patterns in Microbially Induced Calcite Precipitation (MICP)

Ariadni Elmaloglou

The principle of tailoring material properties to improve the mechanical behaviour of soils through compaction or cement grouting dates to the 60s. The increasing trends of urbanization worldwide require new solutions for the development of resilient and s ...

EPFL2023

DESI mock challenge Halo and galaxy catalogues with the bias assignment method

Cheng Zhao, Ginevra Favole, Yu Yu

Context. We present a novel approach to the construction of mock galaxy catalogues for large-scale structure analysis based on the distribution of dark matter halos obtained with effective bias models at the field level. Aims. We aim to produce mock galaxy ...

EDP SCIENCES S A2023

On Smoothed Explanations: Quality and Robustness

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Michail Vlachos, Ahmad Ajalloeian

Explanation methods highlight the importance of the input features in taking a predictive decision, and represent a solution to increase the transparency and trustworthiness in machine learning and deep neural networks (DNNs). However, explanation methods ...

Assoc Computing Machinery2022

Multi-scale approach for the prediction of atomic scale properties

Michele Ceriotti, Jigyasa Nigam, Andrea Grisafi

Electronic nearsightedness is one of the fundamental principles that governs the behavior of condensed matter and supports its description in terms of local entities such as chemical bonds. Locality also underlies the tremendous success of machine-learning ...

2021

Emerging Threats of Synthetic Biology and Biotechnology. Addressing Security and Resilience Issues

Synthetic biology is a field of biotechnology that is rapidly growing in various applications, such as in medicine, environmental sustainability, and energy production. However these technologies also have unforeseen risks and applications to humans and th ...

Springer2021

Pyramid Architecture Search for Real-Time Image Deblurring

Wei Liu, Kaicheng Yu

Multi-scale and multi-patch deep models have been shown effective in removing blurs of dynamic scenes. However, these methods still suffer from one major obstacle: manually designing a lightweight and high-efficiency network is challenging and time-consumi ...

IEEE2021

ActiveMoCap: Optimized Viewpoint Selection for Active Human Motion Capture

Pascal Fua, Mathieu Salzmann, Helge Jochen Rhodin, Sena Kiciroglu, Sudipta Sinha

The accuracy of monocular 3D human pose estimation depends on the viewpoint from which the image is captured. While freely moving cameras, such as on drones, provide control over this viewpoint, automatically positioning them at the location which will yie ...

IEEE2020

A deep learning framework for matching of SAR and optical imagery

Devis Tuia, Sylvain Lobry, Lloyd Haydn Hughes

SAR and optical imagery provide highly complementary information about observed scenes. A combined use of these two modalities is thus desirable in many data fusion scenarios. However, any data fusion task requires measurements to be accurately aligned. Wh ...

2020

Connectome spectral analysis to track EEG task dynamics on a subsecond scale

David Pascucci, Patric Hagmann, Sébastien Tourbier, Gijs Plomp, Michaël Defferrard

We present an approach for tracking fast spatiotemporal cortical dynamics in which we combine white matter connectivity data with source-projected electroencephalographic (EEG) data. We employ the mathematical framework of graph signal processing in order ...

2020

Atomistic modeling of the solid-liquid interface of metals and alloys

Edoardo Baldi

Solidification is a phase transformation of utmost importance in material science, for it largely controls materials' microstructure on which a wide range of mechanical properties depends. Almost every human artifact undergoes a transformation that leads t ...

EPFL2020

Trait-specific dispersal of bacteria in heterogeneous porous environments: from pore to porous medium scale

Tom Ian Battin, Hannes Markus Peter, David Scheidweiler, Filippo Miele

The dispersal of organisms controls the structure and dynamics of populations and communities, and can regulate ecosystem functioning. Predicting dispersal patterns across scales is important to understand microbial life in heterogeneous porous environment ...

2020

Microstructure evolution of stainless steel subjected to biaxial load path changes: In-situ neutron diffraction and multi-scale modeling

Helena Van Swygenhoven

The lattice strain and intensity evolution obtained from in-situ neutron diffraction experiments of 316L cruciform samples subjected to 45 degrees and 90 degrees load path changes are presented and predicted using the multi-scale modeling approach proposed ...

2019

Correlating Oxygen Reduction Reaction Activity and Structural Rearrangements in MgO-Supported Platinum Nanoparticles

Kevin Rossi

We develop a multi-scale approach towards the design of metallic nanoparticles with applications as catalysts in electrochemical reactions. The here discussed method exploits the relationship between nanoparticle architecture and electrochemical activity a ...

2019

Microbial life in porous systems

David Scheidweiler

Microbial life in porous systems dominates the functioning of numerous ecosystems, ranging from stream sediments to soils. While these environments are characterized by structures that vary spatially over orders of magnitude, the traditional research focus ...

EPFL2019

Real-Time Optimization of Uncertain Process Systems via Modifier Adaptation and Gaussian Processes

Dominique Bonvin, Colin Neil Jones, Timm Faulwasser, Harsh Ambarishkumar Shukla, Tafarel de Avila Ferreira

In the context of static real-time optimization, the use of measurements allows dealing with uncertainty in the form of plant-model mismatch and disturbances. Modifier adaptation (MA) is a measurement-based scheme that uses first-order corrections to the m ...

IEEE2018

A toolkit for multi-scale mapping of the solar energy-generation potential of buildings in urban environments under uncertainty

Marilyne Andersen, Emmanuel Rey, Giuseppe Peronato, Parag Rastogi

Many municipalities and public authorities have supported the creation of solar cadastres to map the solar energy-generation potential of existing buildings. Despite advancements in modelling solar potential, most of these tools provide simple evaluations ...

2018

Analyse multi-échelle de n-grammes sur 200 années d'archives de presse

Vincent Christian Buntinx

The recent availability of large corpora of digitized texts over several centuries opens the way to new forms of studies on the evolution of languages. In this thesis, we study a corpus of 4 million press articles covering a period of 200 years. The thesis ...

EPFL2017

Towards the Use of Social Interaction Conventions as Prior for Gaze Model Adaptation

Jean-Marc Odobez, Rémy Alain Siegfried, Yu Yu

Gaze is an important non-verbal cue involved in many facets of social interactions like communication, attentiveness or attitudes. Nevertheless, extracting gaze directions visually and remotely usually suffers large errors because of low resolution images, ...

ACM2017

Multi-material Optoelectronic Fiber Devices

Fabien Sorin, Wei Yan, Alexis Gérald Page, Yunpeng Qu, Marco Volpi

The recent ability to integrate materials with different optical and optoelectronic properties in prescribed architectures within flexible fibers is enabling novel opportunities for advanced optical probes, functional surfaces and smart textiles. In partic ...

SPIE-Int Soc Optical Engineering2017