Publications associées à Nom de domaine internationalisé

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

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, Steffen Schneider, Matthias Bethge, Thomas Ray Biasi, Mert Yüksekgönül

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, Tiago De Freitas Pereira, André Anjos

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