VIVALDI: steel billet tracking with advanced computer vision

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

The fluctuation short pulse reflectometry diagnostic is simulated with the full-wave CUWA code for ad-hoc turbulence and simplified geometry. The nonlinear effects on the measurements are investigated while accounting for the plasma curvature, probing angl ...

Glass powder, a non-degradable waste material, offers significant potential to reduce cement consumption and carbon emissions in concrete production. However, existing mix design methods for glass powder concrete (GPC) fail to systematically balance econom ...

Deep Learning (DL) models processing images to recognize the health state of large infrastructure components can exhibit biases and rely on non-causal shortcuts. eXplainable Artificial Intelligence (XAI) can address these issues but manually analyzing expl ...

Fine-tuning has become a norm to achieve state-of-the-art performance when employing pre-trained networks like foundation models. These models are typically pre-trained on large-scale unannotated data using self-supervised learning (SSL) methods. The SSL-b ...

Accurately and rapidly simulating the hysteretic behavior of double skin composite wall (DSCW) under earthquake loads enhance the efficiency of seismic performance assessments for high-rise steel-concrete composite structures. The application of artificial ...

Measuring perceptual similarity is a key tool in computer vision. In recent years perceptual metrics based on features extracted from neural networks with large and diverse training sets, e.g. CLIP, have become popular. At the same time, the metrics extrac ...

One aspect of the present invention proposes a method of predicting meteorological information by using an artificial deep neural network. The present invention according to one example focuses on image processing, specifically on fusing a plurality of ima ...

Monitoring indoor air quality is important nowdays, as noted by many researchers, since pollution potentially introduces a major impact on the health of people. There are many factors that increase the concentration of a pollutant in a room and there may e ...

Collaborative Machine Learning (CML) allows participants to jointly train a machine learning model while keeping their training data private. In many scenarios where CML is seen as the solution to privacy issues, such as health-related applications, safety ...

Underwater scenes are challenging for computer vision methods due to color degradation caused by the water column and detrimental lighting effects such as caustic caused by sunlight refracting on a wavy surface. These challenges impede widespread use of co ...

Energy-dispersive X-ray spectroscopy (EDXS) mapping with a scanning transmission electron microscope (STEM) is commonly used for chemical characterization of materials. However, STEM-EDXS quantification becomes challenging when the phases constituting the ...

Synthetic data is gaining increasing relevance for training machine learning models. This is mainly motivated due to several factors such as the lack of real data and intra-class variability, time and errors produced in manual labeling, and in some cases p ...

The first evidence for the standard model production of a top quark in association with a W boson and a Z boson is reported. The measurement is performed in multilepton final states, where the Z boson is reconstructed via its decays to electron or muon pai ...

Deep learning models have shown great promise in estimating tissue microstructure from limited diffusion magnetic resonance imaging data. However, these models face domain shift challenges when test and train data are from different scanners and protocols, ...

Microsurgical manipulations are key experimental techniques in life science research, particularly in embryology. These techniques are most often performed manually by highly skilled scientists, posing limitations on speed, precision, and reproducibility. ...

Biometric recognition systems tend toward ubiquity and are widely being used in different applications for authentication purposes. Compared to conventional authentication tools, such as PIN or password, which are always in danger of being forgotten or sto ...

The increasing integration of Machine Learning (ML) techniques into clinical care, driven in particular by Deep Learning (DL) using Artificial Neural Nets (ANNs), promises to reshape medical practice on various levels and across multiple medical fields. Mu ...

Logic Synthesis From Partial Specifications (LSFPS) is the problem of finding the hardware implementation of a Boolean function from a partial knowledge of its care set. The elements missing from the specifications are named don't knows. The exact solution ...

Deep learning (DL) has shown remarkable results in solving inverse problems in various domains. In particular, the Tikhonet approach is very powerful in deconvolving optical astronomical images. However, this approach only uses the l(2) loss, which does no ...

Background After 18 months of responding to the COVID-19 pandemic, there is still no agreement on the optimal combination of mitigation strategies. The efficacy and collateral damage of pandemic policies are dependent on constantly evolving viral epidemiol ...

VIVALDI: steel billet tracking with advanced computer vision

Chattez avec Graph Search

Nonlinear Effects in Fluctuation Short Pulse Reflectometry

Machine Learning-assisted Sustainable Mix Design of Waste Glass Powder Concrete with Strength-cost-co2 Emissions Trade-offs

Automated processing of eXplainable Artificial Intelligence outputs in deep learning models for fault diagnostics of large infrastructures

Emotion information recovery potential of wav2vec2 network fine-tuned for speech recognition task

Machine learning-aided hysteretic response prediction of double skin composite wall under earthquake loads

Adversarially Robust CLIP Models Can Induce Better (Robust) Perceptual Metrics

Meteorological information prediction using images from webcams

Fusing Machine Learning Methods with Computational Fluid Dynamics and Sensor Data for Indoor Air Quality Monitoring

On the Conflict Between Robustness and Learning in Collaborative Machine Learning

Self-Supervised Underwater Caustics Removal and Descattering via Deep Monocular SLAM

Non-negative matrix factorization-aided phase unmixing and trace element quantification of STEM-EDXS data

Second Edition Frcsyn Challenge at Cvpr 2024: Face Recognition Challenge in the Era of Synthetic Data

Evidence for tWZ production in proton-proton collisions at √s=13 TeV in multilepton final states

Cross-Age and Cross-Site Domain Shift Impacts on Deep Learning-Based White Matter Fiber Estimation in Newborn and Baby Brains

A Robotic Surgery Platform for Automated Tissue Micromanipulation in Zebrafish Embryos

On the Information in Deep Biometric Templates: from Vulnerability of Unprotected Templates to Leakage in Protected Templates

Machine learning and its impact on psychiatric nosology: Findings from a qualitative study among German and Swiss experts

Accuracy recovery: A decomposition procedure for the synthesis of partially-specified Boolean functions

ShapeNet: Shape constraint for galaxy image deconvolution

what If...? Pandemic Policy-decision-support to Guide a Cost-benefit-optimised, Country- Specific Response