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Related publications (25)

An interior penalty coupling strategy for isogeometric non-conformal Kirchhoff-Love shell patches

Annalisa Buffa, Pablo Antolin Sanchez, Giuliano Guarino

This work focuses on the coupling of trimmed shell patches using Isogeometric Analysis, based on higher continuity splines that seamlessly meet the

C^1

requirement of Kirchhoff-Love-based discretizations. Weak enforcement of coupling conditions is achiev ...

Springer2024

DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications

Pascal Frossard, Ádám Dániel Ivánkay

Along with the successful deployment of deep neural networks in several application domains, the need to unravel the black-box nature of these networks has seen a significant increase recently. Several methods have been introduced to provide insight into t ...

Assoc Computational Linguistics-Acl2023

Global, Passive Detection of Connection Tampering

Louis-Henri Manuel Jakob Merino

In-network devices around the world monitor and tamper with connections for many reasons, including intrusion prevention, combating spam or phishing, and country-level censorship. Connection tampering seeks to block access to specific domain names or keywo ...

Assoc Computing Machinery2023

Chat2Code: A Chatbot for Model Specification and Code Generation, The Case of Smart Contracts

Shailesh Mishra

The potential of automatic code generation through Model-Driven Engineering (MDE) frameworks has yet to be realized. Beyond their ability to help software professionals write more accurate, reusable code, MDE frameworks could make programming accessible fo ...

Ieee Computer Soc2023

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Mohammad Ali Shaeri

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

2023

Towards versatile conversations with data-driven dialog management and its integration in commercial platforms

Pablo Cañas Castellanos

Conversational interfaces have recently become a ubiquitous element in both the personal sphere by easing access to services, and industrial environments by the automation of services, improved customer support and its corresponding cost savings. However, ...

2021

Pretraining boosts out-of-domain robustness for pose estimation

Alexander Mathis, Mackenzie Mathis, Matthias Bethge, Steffen Schneider

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

Vision based pixel-level bridge structural damage detection using a link ASPP network

Wenlong Deng

Structural Health Monitoring (SHM) has greatly benefited from computer vision. Recently, deep learning approaches are widely used to accurately estimate the state of deterioration of infrastructure. In this work, we focus on the problem of bridge surface s ...

2020

Heterogeneous Face Recognition Using Domain Specific Units

Sébastien Marcel, André Anjos, Tiago De Freitas Pereira

The task of Heterogeneous Face Recognition consists in matching face images that are sensed in different domains, such as sketches to photographs (visual spectra images), thermal images to photographs or near-infrared images to photographs. In this work we ...

2019

Universal Adversarial Attacks on Text Classifiers

Pascal Frossard, Seyed Mohsen Moosavi Dezfooli, Melika Behjati

Despite the vast success neural networks have achieved in different application domains, they have been proven to be vulnerable to adversarial perturbations (small changes in the input), which lead them to produce the wrong output. In this paper, we propos ...

IEEE2019

Handling probabilistic integrity constraints in pay-as-you-go reconciliation of data models

Karl Aberer, Quoc Viet Hung Nguyen, Thành Tâm Nguyên, Zoltán Miklós

Data models capture the structure and characteristic properties of data entities, e.g., in terms of a database schema or an ontology. They are the backbone of diverse applications, reaching from information integration, through peer-to-peer systems and ele ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Feed-forwards meet recurrent networks in vehicle trajectory prediction

Alexandre Massoud Alahi, Mohammadhossein Bahari

For an autonomous car, getting surprised is the worst thing that can happen. To prevent that, plenty of studies are trying to forecast traffic participants’ actions especially in an urban scene using recurrent networks. Recurrent networks are used for temp ...

2019

Learning How To Recognize Faces In Heterogeneous Environments

Tiago De Freitas Pereira

Face recognition is a mature field in biometrics in which several systems have been proposed over the last three decades. Such systems are extremely reliable under controlled recording conditions and it has been deployed in the field in critical tasks, suc ...

EPFL2019

Macroecology in the age of Big Data - Where to go from here?

Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this "Big Data" trend, with a strong rise in the volume of data that we are using for our research. Here, we sum ...

2020

A Too to Design Interactive Characters Based on Embodied Cognition

Ronan Boulic, Joan Llobera Mahy

Creating interactive characters is one of the most challenging tasks of videogame design. In order to facilitate such an endeavor, we introduce a decisional and behavior synthesis architecture integrated in the game engine Unity3D. A distinguishing feature ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Hyperdimensional computing for blind and one-shot classification of EEG error-related potentials

José del Rocio Millán Ruiz

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as “hypervectors,” is a brain-inspired alternative to computing with numbers. HD computing ...

Springer Verlag2020

Hyperdimensional computing for noninvasive brain-computer interfaces: Blind and one-shot classification of EEG error-related potentials

José del Rocio Millán Ruiz

The mathematical properties of high-dimensional (HD) spaces show remarkable agreement with behaviors controlled by the brain. Computing with HD vectors, referred to as "hypervectors," is a brain-inspired alternative to computing with numbers. HD computing ...

2017

A Multi-Core Reconfigurable Architecture for Ultra-Low Power Bio-Signal Analysis

David Atienza Alonso, Giovanni Ansaloni, Ruben Braojos Lopez, Soumya Subhra Basu, Loris Gérard Duch

This paper introduces a novel computing architecture devoted to the ultra-low power analysis of multiple bio-signals. Its structure comprises several processors interfaced with a shared acceleration resource, implemented as a Coarse Grained Reconfigurable ...

2016

Engineered a/c domain patterns in multilayer (110) epitaxial Pb(Zr,Ti)O-3 thin films: Impact on domain compliance and piezoelectric properties

Nava Setter, Silviu Cosmin Sandu, Andrea Mazzalai, Mahamudu Mtebwa

While there is extensive literature on the influence of both compressive and tensile strain on the domain patterns of (001) tetragonal ferroelectric thin films, little is known regarding domain engineering in (110) films. The primary reason is the absence ...

2016

Adaptation and coaching of periodic motion primitives through physical and visual interaction

Tadej Petric

In this paper we propose and evaluate a control system to (1) learn and (2) adapt robot motion for continuous non-rigid contact with the environment. We present the approach in the context of wiping surfaces with robots. Our approach is based on learning b ...

Elsevier2016