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Domaine de premier niveau générique

Publications associées (54)

DARE: Towards Robust Text Explanations in Biomedical and Healthcare Applications

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

A 3D indicator for guiding AI applications in the energy sector

Christophe Ballif, Alessandro Francesco Aldo Virtuani, Hugo James André Quest, Marine Dominique Cauz, Fabian Heymann, Laure-Emmanuelle Perret Aebi, Christian Rod

The utilisation of Artificial Intelligence (AI) applications in the energy sector is gaining momentum, with increasingly intensive search for suitable, high-quality and trustworthy solutions that displayed promising results in research. The growing interes ...

2022

Pyramid Architecture Search for Real-Time Image Deblurring

Wei Liu, Kaicheng Yu

Multi-scale and multi-patch deep models have been shown effective in removing blurs of dynamic scenes. However, these methods still suffer from one major obstacle: manually designing a lightweight and high-efficiency network is challenging and time-consumi ...

IEEE2021

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

Pareto-like sequential sampling heuristic for global optimisation

Katrin Beyer, Mahmoud S. M. Shaqfa

In this paper, we propose a simple global optimisation algorithm inspired by Pareto’s principle. This algorithm samples most of its solutions within prominent search domains and is equipped with a self-adaptive mechanism to control the dynamic tightening o ...

2021

Language model domain adaptation for automatic speech recognition

Petr Motlicek, Amrutha Prasad

This report provides an overview of the work carried out in improving Language Model (LM) development used during the decoding of an Automatic Speech Recognition (ASR) system. The goal of this work is to develop a robust language model that can be adapted ...

Idiap2020

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

GeoFarmer: A monitoring and feedback system for agricultural development projects

Claudia Rebeca Binder Signer

Farmers can manage their crops and farms better if they can communicate their experiences, both positive and negative, with each other and with experts. Digital agriculture using internet communication technology (ICT) may facilitate the sharing of experie ...

ELSEVIER SCI LTD2019

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

Karl Aberer, 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

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