Publication

MulT: An End-to-End Multitask Learning Transformer

Publications associées (36)

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Remote sensing visual question answering (RSVQA) opens new avenues to promote the use of satellites data, by interfacing satellite image analysis with natural language processing. Capitalizing on the remarkable advances in natural language processing and c ...

2022

Linear and nonlinear excitation of TAE modes by external electromagnetic perturbations using ORB5

Laurent Villard, Emmanuel Lanti, Alberto Bottino, Mohsen Sadr

The excitation of toroidicity-induced Alfven eigenmodes (TAEs) using prescribed external electromagnetic perturbations (hereafter 'antenna') acting on a confined toroidal plasma, as well as its nonlinear couplings to other modes in the system, is studied. ...

IOP Publishing Ltd2022

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Estimating the pose of multiple animals is a challenging computer vision problem: frequent interactions cause occlusions and complicate the association of detected keypoints to the correct individuals, as well as having highly similar looking animals that ...

NATURE PORTFOLIO2022

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Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

2021

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Decentralized deployment of drone swarms usually relies on inter-agent communication or visual markers that are mounted on the vehicles to simplify their mutual detection. This letter proposes a vision-based detection and tracking algorithm that enables gr ...

2021

Lattice-Free Mmi Adaptation Of Self-Supervised Pretrained Acoustic Models

Hervé Bourlard, Apoorv Vyas

In this work, we propose lattice-free MMI (LFMMI) for supervised adaptation of self-supervised pretrained acoustic model. We pretrain a Transformer model on thousand hours of untranscribed Librispeech data followed by supervised adaptation with LFMMI on th ...

IEEE2021

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Transformers have been proven a successful model for a variety of tasks in sequence modeling. However, computing the attention matrix, which is their key component, has quadratic complexity with respect to the sequence length, thus making them prohibitivel ...

2020

Assessing Public Opinion on CRISPR-Cas9: Combining Crowdsourcing and Deep Learning

Marcel Salathé, Martin Müller

Background: The discovery of the CRISPR-Cas9-based gene editing method has opened unprecedented new potential for biological and medical engineering, sparking a growing public debate on both the potential and dangers of CRISPR applications. Given the speed ...

JMIR PUBLICATIONS, INC2020

DISK: learning local features with policy gradient

Pascal Fua, Eduard Trulls Fortuny, Michal Jan Tyszkiewicz

Local feature frameworks are difficult to learn in an end-to-end fashion, due to the discreteness inherent to the selection and matching of sparse keypoints. We introduce DISK (DIScrete Keypoints), a novel method that overcomes these obstacles by leveragin ...

2020

Self-attention for Speech Emotion Recognition

Philip Neil Garner, Lorenzo Tarantino

Speech Emotion Recognition (SER) has been shown to benefit from many of the recent advances in deep learning, including recurrent based and attention based neural network architectures as well. Nevertheless, performance still falls short of that of humans. ...

2019

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