Publications associées à Sensor and the Beast: Generalised Methods to Recognise Animal Behaviour and Quantify Energy Expenditure Using Inertial Sensors, and Applications

Publications associées (40)

Mitigating imaging systematics for DESI 2024 emission Line Galaxies and beyond

Emission Line Galaxies (ELGs) are one of the main tracers that the Dark Energy Spectroscopic Instrument (DESI) uses to probe the universe. However, they are afflicted by strong spurious correlations between target density and observing conditions known as ...

IOP Publishing2025

Unsupervised Multi-view UAV Image Geo-localization via Iterative Rendering

Chang Xu, Li Mi

Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) poses significant challenges due to the substantial view discrepancies between oblique UAV images and overhead satellite images. Existing methods heavily rely on supervised learning with labe ...

2025

Universal Neural-Cracking-Machines: Self-Configurable Password Models from Auxiliary Data

Carmela González Troncoso, Dario Pasquini

We introduce the concept of "universal"password model - a password model that, once pre-trained, can automatically adapt its guessing strategy based on the target system. To achieve this, the model does not need to access any plaintext passwords from the t ...

Institute of Electrical and Electronics Engineers Inc.2024

“But of course i’m going to look happy” or “He needed to know I was angry”? Comparing use of emotional labour in teamwork in engineering and hospitality students

Roland John Tormey, Nihat Kotluk

Being able to work effectively in a team is a vital professional skill but how do students in different disciplines, engineering and hospitality, display their emotions when working together? We investigated their self-reported use of emotional labour stra ...

EAPRIL - European Association for Practitioner Research on Improving Learning2024

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Jan Skaloud, Davide Antonio Cucci, Aurélien Arnaud Brun, Kyriaki Mouzakidou

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

2024

Cross-transfer Knowledge between Speech and Text Encoders to Evaluate Customer Satisfaction

Tilak Purohit

Customer Satisfaction (CS) in call centers influences customer loyalty and the company's reputation. Traditionally, CS evaluations were conducted manually or with classical machine learning algorithms; however, advancements in deep learning have led to aut ...

International Speech Communication Association2024

Physics-informed neural network estimation of material properties in soft tissue nonlinear biomechanical models

Alfio Quarteroni

The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the interpretation of clinical data. However, high-resolution and accurate multi-p ...

SPRINGER2024

Where the White Continent Is Blue: Deep Learning Locates Bare Ice in Antarctica

Devis Tuia, Marc Conrad Russwurm

In some areas of Antarctica, blue-colored bare ice is exposed at the surface. These blue ice areas (BIAs) can trap meteorites or old ice and are vital for understanding the climatic history. By combining multi-sensor remote sensing data (MODIS, RADARSAT-2, ...

Amer Geophysical Union2024

Perceived impacts of the Fridays for Future climate movement on environmental concern and behaviour in Switzerland

Blanche Thérèse Marie Philippe Dalimier, Claudia Rebeca Binder Signer, Livia Bianca Fritz, Ralph Hansmann

Calling for increased action on climate change, Fridays for Future (FFF) quickly gained momentum around the world and became highly visible through strikes and protests in more than 150 countries. Considering its scale and magnitude, questions about the im ...

2023

The impact of different methods of increasing the intensity of compassion in engineering ethics cases

Roland John Tormey, Nihat Kotluk

Despite the growing interest in emotions in engineering education, empirical research on incorporating them into engineering ethics education is limited. Therefore, we designed this experimental study to assess how different methods for integrating compass ...

2024

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Jan Skaloud, Aman Sharma, Gabriel François Laupré

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

2024

Compassion and Engineering Students’ Moral Reasoning: The Emotional Experience of Engineering Ethics Cases

Roland John Tormey, Nihat Kotluk

Background: There has been an increase in interest in emotion in engineering and science ethics education. There is also evidence that emotional content in case studies may improve students’ learning and enhance awareness, understanding, and motivation con ...

American Society for Engineering Education2023

Stabilization of nonlinear systems by neural Lyapunov approximators and Sontag's formula

Adriano Mele

This note describes a method to train a Neural Network so that it approximates a control Lyapunov function for a nonlinear system in affine form. The network is trained in a physics-informed fashion, as the training data are generated by enforcing the nega ...

Institute of Electrical and Electronics Engineers Inc.2024

Deep learning-based recommendation system for metal-organic frameworks (MOFs)

Berend Smit, Kevin Maik Jablonka, Xiaoqi Zhang

This work presents a recommendation system for metal-organic frameworks (MOFs) inspired by online content platforms. By leveraging the unsupervised Doc2Vec model trained on document-structured intrinsic MOF characteristics, the model embeds MOFs into a hig ...

Royal Soc Chemistry2024

Engineering Materials for Neurotechnology

Diego Ghezzi

Neurotechnology applies methods and devices to mitigate the burden of neurological and mental disorders. In particular, neural interfaces establish a long-term, seamless, symbiotic integration between implants and neural tissue. Materials play a pivotal ro ...

WILEY-V C H VERLAG GMBH2023

An Ultralow-Power Triaxial MEMS Accelerometer With High-Voltage Biasing and Electrostatic Mismatch Compensation

Kyojin Choo

This article presents a triaxial micro electromechani-cal system (MEMS) capacitive accelerometer using a high-voltage biasing technique to achieve high resolution with ultralow power. The accelerometer system generates a differential pair of high voltages ...

Ieee-Inst Electrical Electronics Engineers Inc2024

From Nano to Macro An overview of the IEEE Bio Image and Signal Processing Technical Committee

Michaël Unser, Dimitri Nestor Alice Van De Ville, Michael Stefan Daniel Liebling

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Robust machine learning for neuroscientific inference

Steffen Schneider

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

EPFL2024

Hardware Implementation of Digital Signal Processing Algorithms for Programmable Epilepsy Control Systems

Keyvan Farhang Razi

Epilepsy is a common chronic neurological disorder that causes recurring seizures and affects more than 50 million people worldwide. Implantable medical devices (IMDs) are regarded as effective tools to cure patients who suffer from refractory epilepsy. Se ...

EPFL2023

Uncertainty quantification by direct propagation of shallow ensembles

Michele Ceriotti, Matthias Linus Kellner

Statistical learning algorithms provide a generally-applicable framework to sidestep time-consuming experiments, or accurate physics-based modeling, but they introduce a further source of error on top of the intrinsic limitations of the experimental or the ...

2024