Ghent University Academic Bibliography

Conference Paper
C1
open access

Improved deep learning based ECG classification through automated feature selection and weighted loss function

Timo De Waele (UGent) , Daniel Peralta (UGent) , Eli De Poorter (UGent) and Adnan Shahid (UGent)

(2024) 2024 International Joint Conference on Neural Networks (IJCNN). In Proceedings of International Joint Conference on Neural Networks 3. p.1-8

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Conference Paper
P1
open access

An homeostatic activity-dependent structural plasticity algorithm for richer input combination

Tanguy Cazalets (UGent) and Joni Dambre (UGent)

(2023) 2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN. In IEEE International Joint Conference on Neural Networks (IJCNN)

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Conference Paper
P1
open access

Delay-sensitive local plasticity in echo state networks

Stefan-Teodor Iacob (UGent) , Spyridon Chavlis, Panayiota Poirazi and Joni Dambre (UGent)

(2023) 2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN. In IEEE International Joint Conference on Neural Networks (IJCNN)

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Conference Paper
P1
open access

Relation-guided acoustic scene classification aided with event embeddings

Yuanbo Hou (UGent) , Bo Kang (UGent) , Wout Van Hauwermeiren (UGent) and Dick Botteldooren (UGent)

(2022) 2022 International Joint Conference on Neural Networks (IJCNN). In Proceedings of International Joint Conference on Neural Networks

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Conference Paper
P1
open access

Sensor characterization for supporting de-noising and auto-calibration of sensor data

Wout Van Hauwermeiren (UGent) , Yuanbo Hou (UGent) , Karlo Filipan and Dick Botteldooren (UGent)

(2022) 2022 International Joint Conference on Neural Networks (IJCNN). In Proceedings of International Joint Conference on Neural Networks

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Conference Paper
P1
open access

Spikemax : spike-based loss methods for classification

Sumit Bam Shrestha, Longwei Zhu and Pengfei Sun (UGent)

(2022) 2022 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). In IEEE International Joint Conference on Neural Networks (IJCNN)

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Conference Paper
P1
open access

Dynamic narrowing of VAE bottlenecks using GECO and L0 regularization

Cedric De Boom, Samuel Wauthier (UGent) , Tim Verbelen (UGent) and Bart Dhoedt (UGent)

(2021) 2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). In IEEE International Joint Conference on Neural Networks (IJCNN)

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Conference Paper
P1
open access

Not all adversarial examples require a complex defense : identifying over-optimized adversarial examples with IQR-based logit thresholding

Utku Özbulak, Arnout Van Messem (UGent) and Wesley De Neve (UGent)

(2019) 2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN).

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Conference Paper
P1
open access

Towards using reservoir computing networks for noise-robust image recognition

Azarakhsh Jalalvand (UGent) , Wesley De Neve (UGent) , Rik Van de Walle (UGent) and Jean-Pierre Martens (UGent)

(2016) 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). In IEEE International Joint Conference on Neural Networks (IJCNN) p.1666-1672

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Conference Paper
P1
open access

Resource-constrained classification using a cascade of neural network layers

Sam Leroux (UGent) , Steven Bohez (UGent) , Tim Verbelen (UGent) , Bert Vankeirsbilck (UGent) , Pieter Simoens (UGent) and Bart Dhoedt (UGent)

(2015) IEEE International Joint Conference on Neural Networks (IJCNN). p.1-7

Academic Bibliography

Improved deep learning based ECG classification through automated feature selection and weighted loss function

An homeostatic activity-dependent structural plasticity algorithm for richer input combination

Delay-sensitive local plasticity in echo state networks

Relation-guided acoustic scene classification aided with event embeddings

Sensor characterization for supporting de-noising and auto-calibration of sensor data

Spikemax : spike-based loss methods for classification

Dynamic narrowing of VAE bottlenecks using GECO and L0 regularization

Not all adversarial examples require a complex defense : identifying over-optimized adversarial examples with IQR-based logit thresholding

Towards using reservoir computing networks for noise-robust image recognition

Resource-constrained classification using a cascade of neural network layers

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