Results 21 to 30 of about 609,343 (292)
Fall Detection Using Multimodal Data
, 2022 12 pages, 5 figures, 6 ...
Thao V. Ha +4 more
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Disease Knowledge Transfer across Neurodegenerative Diseases [PDF]
, 2019 We introduce Disease Knowledge Transfer (DKT), a novel technique for transferring biomarker information between related neurodegenerative diseases. DKT infers robust multimodal biomarker trajectories in rare neurodegenerative diseases even when only ...
Alexander, Daniel C. +10 more
core +4 more sources
Distributed efficient multimodal data clustering [PDF]
2017 25th European Signal Processing Conference (EUSIPCO), 2017 Publication in the conference proceedings of EUSIPCO, Kos island, Greece ...
Jia Chen 0002, Ioannis D. Schizas
openaire +2 more sources
Using a Bayesian averaging model for estimating the reliability of decisions in multimodal biometrics [PDF]
, 2006 The issue of reliable authentication is of increasing importance in modern society. Corporations, businesses and individuals often wish to restrict access to logical or physical resources to those with relevant privileges.
Maple, Carsten, Schetinin, Vitaly
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Challenges In Multimodal Data Fusion
, 2014 Publication in the conference proceedings of EUSIPCO, Lisbon, Portugal ...
Lahat, Dana +2 more
openaire +4 more sources
Multimodal Data Fusion in Learning Analytics: A Systematic Review
Sensors, 2020 Multimodal learning analytics (MMLA), which has become increasingly popular, can help provide an accurate understanding of learning processes. However, it is still unclear how multimodal data is integrated into MMLA.
Su Mu, Meng Cui, Xiaodi Huang
doaj +1 more source
Comparing two haptic interfaces for multimodal graph rendering [PDF]
, 2002 This paper describes the evaluation of two multimodal interfaces designed to provide visually impaired people with access to various types of graphs. The interfaces consist of audio and haptics which is rendered on commercially available force feedback ...
Brewster, S.A., Yu, W.
core +1 more source
Deep Multimodal Representation Learning from Temporal Data
, 2017 In recent years, Deep Learning has been successfully applied to multimodal learning problems, with the aim of learning useful joint representations in data fusion applications.
Bernal, Edgar A. +5 more
core +1 more source
A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data [PDF]
, 2015 Topic modeling based on latent Dirichlet allocation (LDA) has been a framework of choice to deal with multimodal data, such as in image annotation tasks.
Larochelle, Hugo +2 more
core +1 more source
Does Multimodality Help Human and Machine for Translation and Image Captioning?
, 2016 This paper presents the systems developed by LIUM and CVC for the WMT16 Multimodal Machine Translation challenge. We explored various comparative methods, namely phrase-based systems and attentional recurrent neural networks models trained using ...
Aransa, Walid +7 more
core +1 more source