Publications associées à Exploring Masked Autoencoders for Sensor-Agnostic Image Retrieval in Remote Sensing

Publications associées (15)

Efficiency of neural quantum states in light of the quantum geometric tensor

Neural quantum state (NQS) ans & auml;tze have shown promise in variational Monte Carlo algorithms by their theoretical capability of representing any quantum state. However, the reason behind the practical improvement in their performance with an increase ...

NATURE PORTFOLIO2025

Deep Non-Rigid Structure-From-Motion: A Sequence-to-Sequence Translation Perspective

Tong Zhang

Directly regressing the non-rigid shape and camera pose from the individual 2D frame is ill-suited to the Non-Rigid Structure-from-Motion (NRSfM) problem. This frame-by-frame 3D reconstruction pipeline overlooks the inherent spatial-temporal nature of NRSf ...

2024

Machine learning-based prediction of fish acute mortality: implementation, interpretation, and regulatory relevance

Fernando Perez Cruz

Regulation of chemicals requires knowledge of their toxicological effects on a large number of species, which has traditionally been acquired through in vivo testing. The recent effort to find alternatives based on machine learning, however, has not focuse ...

2024

Generative AI-Enabled Conversational Interaction to Support Self-Directed Learning Experiences in Transversal Computational Thinking

Denis Gillet, Adrian Christian Holzer, Juan Carlos Farah, Abdessalam Ouaazki

As computational thinking (CT) becomes increasingly acknowledged as an important skill in education, self-directed learning (SDL) emerges as a key strategy for developing this capability. The advent of generative AI (GenAI) conversational agents has disrup ...

2024

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Ariane Andrée Marie Delrocq, Sahand Jamal Rahi

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Publishing Group2023

The Facets of Intangible Heritage in Southern Chinese Martial Arts: Applying a Knowledge-Driven Cultural Contact Detection Approach

Yumeng Hou

Investigating the intangible nature of a cultural domain can take multiple forms, addressing for example the aesthetic, epistemic and social dimensions of its phenomenology. The context of Southern Chinese martial arts is of particular significance as it c ...

Association for Computing Machinery2023

On Triangulation as a Form of Self-Supervision for 3D Human Pose Estimation

Pascal Fua, Sina Honari, Leonardo Citraro, Soumava Kumar Roy

Supervised approaches to 3D pose estimation from single images are remarkably effective when labeled data is abundant. However, as the acquisition of ground-truth 3D labels is labor intensive and time consuming, recent attention has shifted towards semi- a ...

IEEE2022

Relative stability toward diffeomorphisms indicates performance in deep nets

Matthieu Wyart, Mario Geiger, Leonardo Petrini, Alessandro Favero

Understanding why deep nets can classify data in large dimensions remains a challenge. It has been proposed that they do so by becoming stable to diffeomorphisms, yet existing empirical measurements support that it is often not the case. We revisit this qu ...

IOP Publishing Ltd2022

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association

Alexandre Massoud Alahi, Sven Kreiss, Lorenzo Bertoni

Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoi ...

IEEE Institute of Electrical and Electronics Engineers2022

Multi-fidelity surrogate modeling using long short-term memory networks

Jan Sickmann Hesthaven

When evaluating quantities of interest that depend on the solutions to differential equations, we inevitably face the trade-off between accuracy and efficiency. Especially for parametrized, time-dependent problems in engineering computations, it is often t ...

ELSEVIER SCIENCE SA2022

Latent Mechanisms of Polarization Switching from In Situ Electron Microscopy Observations

Vasiliki Tileli, Reinis Ignatans

In situ scanning transmission electron microscopy enables observation of the domain dynamics in ferroelectric materials as a function of externally applied bias and temperature. The resultant data sets contain a wealth of information on polarization switch ...

WILEY-V C H VERLAG GMBH2022

Generative Adversarial Networks for Localized Vibrotactile Feedback in Haptic Surfaces

Yves Perriard, Paolo Germano, Adrien Jean-Michel Thabuis, Jonathan André Jean-Marie Chavanne, Xiaotao Ren, Camilo Hernandez Mejia

Touch-screens are the most relevant interface in the context of human-computer interaction. Moreover, they are widely used as interaction means for digital musical instruments, where a complex action-perception loop is involved in the user experience. This ...

IEEE2021

Big-Data Science in Porous Materials: Materials Genomics and Machine Learning

Berend Smit, Seyedmohamad Moosavi, Daniele Ongari, Kevin Maik Jablonka

By combining metal nodes with organic linkers we can potentially synthesize millions of possible metal–organic frameworks (MOFs). The fact that we have so many materials opens many exciting avenues but also create new challenges. We simply have too many ma ...

2020

Design and control of a prototype structure that adapts to loading through large shape changes

Ian Smith, Gennaro Senatore, Arka Prabhata Reksowardojo

This paper reports on experimental testing that was carried out on a prototype adaptive structure designed to counteract the effect of loading through controlled large shape changes. The prototype is 6.6 m truss equipped with 12 linear actuators which has ...

ELSEVIER2020

Resting-state EEG topographies: Reliable and sensitive signatures of unilateral spatial neglect

Dimitri Nestor Alice Van De Ville, Elvira Pirondini

Theoretical advances in the neurosciences are leading to the development of an increasing number of proposed interventions for the enhancement of functional recovery after brain damage. Integration of these novel approaches in clinical practice depends on ...

2020