The influence of data on adversarial robustness

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Treating Noise and Anomalies in Vehicle Trajectories From an Experiment With a Swarm of Drones

Nikolaos Geroliminis, Emmanouil Barmpounakis

Unmanned aerial systems, known as "drones", are relatively new in collecting traffic data. Data from drone videography can have potential applications for traffic research. Drones can record the vehicles from their aerial point-of-view and provide their na ...

IEEE Institute of Electrical and Electronics Engineers2023

Implicit phonetic information modeling for speech emotion recognition

Tilak Purohit

This study investigates the efficacy of utilizing embedding spaces to model phonetic information in emotion utterances for speech emotion recognition. Our approach involves implicit modeling of phone information by deriving phone-based embeddings from netw ...

Isca-Int Speech Communication Assoc2023

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore

Hilal Lashuel, Matteo Dal Peraro, Anass Chiki, Chan Cao, Lucien Fabrice Krapp, Pedro José Santana Ribeiro Magalhães, Juan Francisco Bada Juarez, Verena Rukes, Simon Finn Mayer

Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. ...

Amer Chemical Soc2023

Learnable Wavelet Transform and Domain Adversarial Learning for Enhanced Bearing Fault Diagnosis

Olga Fink, Gaëtan Michel Frusque, Qi Li

The application of unsupervised domain adaptation (UDA)-based fault diagnosis methods has shown significant efficacy in industrial settings, facilitating the transfer of operational experience and fault signatures between different operating conditions, di ...

Research Publishing2023

Bridging structural MRI with cognitive function for individual level classification of early psychosis via deep learning

Lijing Xin

IntroductionRecent efforts have been made to apply machine learning and deep learning approaches to the automated classification of schizophrenia using structural magnetic resonance imaging (sMRI) at the individual level. However, these approaches are less ...

FRONTIERS MEDIA SA2023

Machine-learning accelerated identification of exfoliable two-dimensional materials

Kumar Varoon Agrawal, Giovanni Pizzi, Mohammad Tohidivahdat

Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and effici ...

IOP Publishing Ltd2022

Learning physics-consistent particle interactions

Olga Fink, David Simon Kammer

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

2022