Ghent University Academic Bibliography

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Iterative neural networks for adaptive inference on resource-constrained devices

Sam Leroux (UGent) , Tim Verbelen (UGent) , Pieter Simoens (UGent) and Bart Dhoedt (UGent)

(2022) NEURAL COMPUTING & APPLICATIONS. p.1-16
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Patient activity recognition using radar sensors and machine learning

Geethika Bhavanasi (UGent) , Lorin Werthen-Brabants (UGent) , Tom Dhaene (UGent) and Ivo Couckuyt (UGent)

(2022) NEURAL COMPUTING & APPLICATIONS.
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- Journal Article
- A1
- open access
Leveraging the Bhattacharyya coefficient for uncertainty quantification in deep neural networks

Pieter Van Molle (UGent) , Tim Verbelen (UGent) , Bert Vankeirsbilck (UGent) , Jonas De Vylder (UGent) , Bart Diricx, Tom Kimpe, Pieter Simoens (UGent) and Bart Dhoedt (UGent)

(2021) NEURAL COMPUTING & APPLICATIONS. 33(16). p.10259-10275
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- Journal Article
- A1
- open access
Indoor human activity recognition using high-dimensional sensors and deep neural networks

Baptist Vandersmissen, Nicolas Knudde, Azarakhsh Jalalvand (UGent) , Ivo Couckuyt (UGent) , Tom Dhaene (UGent) and Wesley De Neve (UGent)

(2020) NEURAL COMPUTING & APPLICATIONS. 32(16). p.12295-12309
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- Journal Article
- A1
- open access
Character-level recurrent neural networks in practice : comparing training and sampling schemes

Cedric De Boom (UGent) , Thomas Demeester (UGent) and Bart Dhoedt (UGent)

(2019) NEURAL COMPUTING & APPLICATIONS. 31(8). p.4001-4017
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Sequential modeling of a low noise amplifier with neural networks and active learning

Dirk Gorissen (UGent) , Luciano De Tommasi, Karel Crombecq and Tom Dhaene (UGent)

(2009) NEURAL COMPUTING & APPLICATIONS. 18(5). p.485-494

Academic Bibliography

Iterative neural networks for adaptive inference on resource-constrained devices

Patient activity recognition using radar sensors and machine learning

Leveraging the Bhattacharyya coefficient for uncertainty quantification in deep neural networks

Indoor human activity recognition using high-dimensional sensors and deep neural networks

Character-level recurrent neural networks in practice : comparing training and sampling schemes

Sequential modeling of a low noise amplifier with neural networks and active learning

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