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Communications at Scientific Conferences or Symposia

Recent ETRO Conference Publications

These are ETRO's conference publications for the last three years. A non time-limited list can be found here.

Click here for this list in essential format.

2020

&. Faluvégi, Q. Bolsee, S. Nedevschi, V. Dadarlat and A. Munteanu, “A 3D Convolutional Neural Network for Light Field Depth Estimation,” in 2019 International Conference on 3D Immersion (IC3D), Jan. 2020, pp. 5.

P. Schelkens, A. Gilles, S. Mahmoudpour, K. Oh, C. Perra and A. Pinheiro, “Standardization of Holographic Compression: JPEG Pleno,” in Digital Holography and Three-Dimensional Imaging 2020, Optical Society of America, 2020, pp. 2.

F. Temmermans, A. Kuzma, S. Choi and P. Schelkens, “Adopting the JPEG systems layer to create interoperable imaging ecosystems,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020.

F. Temmermans, D. Bhowmik, F. Pereira, T. Ebrahimi and P. Schelkens, “Exploration of Media Blockchain Technologies for JPEG Privacy and Security,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020.

D. Blinder and P. Schelkens, “Accelerating phase-added stereogram calculations by coefficient grouping for digital holography,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020, pp. 10.

E. Papavasileiou, J. Cornelis and B. Jansen, “Behavior-based Speciation in Classification with NeuroEvolution,” in 2020 IEEE World Congress on Computational Intelligence, Sep. 2020, pp. 7.

J. Ceranka, F. Lecouvet, J. De Mey and J. Vandemeulebroucke, “Computer-aided detection of focal bone metastases from whole-body multi-modal MRI,” in SPIE Medical Imaging 2020, SPIE, Mar. 2020, pp. 7.

Z. Zong, X. Tang, J. Nguyen, K. Khalaf, G. Mangraviti, Y. Liu and P. Wambacq, “A 28GHz Two-Way Current Combining Stacked-FET Power Amplifier in 22nm FD-SOI,” in 2020 IEEE Custom Integrated Circuits Conference (CICC), Mar. 2020, pp. 4.

Z. Zong, X. Tang, K. Khalaf, D. Yan, G. Mangraviti, J. Nguyen, Y. Liu and P. Wambacq, “A 28GHz Voltage-Combined Doherty Power Amplifier with a Compact Transformer-based Output Combiner in 22nm FD-SOI,” in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), IEEE, Aug. 2020.

T. Do, E. Rodrigo, X. Qin, J. Hofman, M. Nikolaou, V. Panzica La Manna, W. Philips and N. Deligiannis, “Deep-Learning-based Hyperlocal Air Quality Monitoring for Smart Cities,” in 10th International Congress on Environmental Modelling and Software (iEMSs 2020), Sep. 2020.

T. Do, D. Nguyen and N. Deligiannis, “Graph Auto-encoder For Graph Signal Denoising,” in 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, May. 2020, pp. 5.

I. Dirks, M. Keyaerts, B. Neyns and J. Vandemeulebroucke, “Automated threshold selection on whole-body 18F-FDG PET/CT for assessing tumor metabolic response,” in SPIE Medical Imaging 2020, Mar. 2020, pp. 7.

S. Mahmoudpour and P. Schelkens, “Cross Data Set Performance Consistency of Objective Quality Assessment Methods for Light Fields,” in 12th International Conference on Quality of Multimedia Experience, QoMEX 2020, Institute of Electrical and Electronics Engineers Inc, May. 2020, pp. 6.

P. Gonidakis, B. Jansen and J. Vandemeulebroucke, “Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification,” in SPIE Medical Imaging 2020, Mar. 2020, pp. 6.

P. Renukaswamy, N. Markulic, S. Park, A. Kankuppe Raghavendra Swamy, Q. Shi, P. Wambacq and J. Craninckx, “A 12mW 10GHz FMCW PLL Based on an Integrating DAC with 90kHz rms Frequency Error for 23MHz/Ás Slope and 1.2GHz Chirp Bandwidth,” in 2020 International Solid-State Circuits Conference, San Francisco: Institute of Electrical and Electronics Engineers ( IEEE ), Feb. 2020, pp. 3.

I. Schiopu and A. Munteanu, “A Study of Prediction Methods based on Machine Learning Techniques for Lossless Image Coding,” in IEEE International Conference on Image Processing, Abu Dhabi, United Arab Emirates: IEEE, Sep. 2020, pp. 5.

I. Schiopu, H. Huang and A. Munteanu, “A Study of Deep-Learning-based Prediction Methods for Lossless Coding,” in 28th European Signal Processing Conference, IEEE, May. 2020, pp. 5.

A. Gasser, T. Lapauw, H. Ingelberts, W. Hoving and M. Kuijk, “Compact time-resolved fluorescence spectrometer,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020, pp. 10.

I. Marivani, E. Tsiligianni, B. Cornelis and N. Deligiannis, “Designing CNNs for Multimodal Image Super-Resolution via the Method of Multipliers,” in 28th European Signal Processing Conference, IEEE, 2020, pp. 5.

I. Marivani, E. Tsiligianni, B. Cornelis and N. Deligiannis, “Joint Image Super-Resolution Via Recurrent Convolutional Neural Networks With Coupled Sparse Priors,” in IEEE International Conference on Image Processing, IEEE, 2020, pp. 5.

S. Park, A. Kankuppe Raghavendra Swamy, P. Renukaswamy, D. Guermandi, A. Visweswaran, J. C. Garcia, S. Sinha, P. Wambacq and J. Craninckx, “A 62mW 60GHz FMCW Radar in 28nm CMOS,” in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), Institute of Electrical and Electronics Engineers ( IEEE ), Aug. 2020, pp. 4.

H. Huang, I. Schiopu and A. Munteanu, “Low-Complexity Angular Intra-Prediction Con-volutional Neural Network for Lossless HEVC,” in IEEE International Workshop on Multimedia Signal Processing, Tampere, Jul. 2020, pp. 6.

R. Kizhakkumkara, P. Schelkens, P. Stepien and M. Kujawinska, “Hologram compression in quantitative phase imaging,” in Proc. SPIE 11249, Feb. 2020.

R. Kizhakkumkara, P. Stepien, D. Blinder, P. Schelkens and M. Kujawinska, “Holographic data compression for holographic microscopy and tomography in biomedical applications,” in OSA Imaging and Applied Optics Congress, Optical Society of America, 2020.

Y. Yang, P. Xiao, B. Liao and N. Deligiannis, “A Robust Deep Unfolded Network for Sparse Signal Recovery from Noisy Binary Measurements,” in European Signal Processing Conference, IEEE, 2020, pp. 5.

E. Rodrigo, D. Nguyen and N. Deligiannis, “Temporal Collaborative Filtering with Graph Convolutional Neural Networks,” in International Conference on Pattern Recognition (ICPR), 2020.

X. Yang, G. Bekoulis and N. Deligiannis, “imec-ETRO-VUB at W-NUT 2020 Shared Task-3: A Multilabel BERT-based system for predicting COVID-19 events,” in Conference on Empirical Methods in Natural Language Processing (and forerunners) (2020), Association for Computational Linguistics, Nov. 2020, pp. 9.

A. Ahar, S. Mahmoudpour, O. Watanabe, D. Taubman and P. Schelkens, “Parameterization of the quality factor for the high throughput JPEG 2000,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020.

A. Grill, E. Bury, J. Michl, S. Tyaginov, D. Linten, T. Grasser, B. Parvais, B. Kaczer, M. Waltl and I. Radu, “Reliability and Variability of Advanced CMOS Devices at Cryogenic Temperatures,” in 2020 IEEE International Reliability Physics Symposium, IRPS 2020, Institute of Electrical and Electronics Engineers Inc, Apr. 2020, pp. 6.

A. Sóñora, P. Gonidakis, B. Jansen, J. Carlos Garcia Naranjo and J. Vandemeulebroucke, “Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework,” in SPIE Medical Imaging 2020, Mar. 2020, pp. 7.

B. Fransen, F. Temmermans and C. Currie, “Imaging techniques and methodologies for acquisition, processing and distribution of multimodal image data of the oeuvre of Jan van Eyck,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020.

B. Oniga, V. Dadarlat and A. Munteanu, “Application-level authentication and encryption atop Bluetooth stack for sensitive data communication,” in 2020 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR), 2020, pp. 5.

C. Perra, P. Garcia Freitas, I. Seidel and P. Schelkens, “An overview of the emerging JPEG Pleno standard, conformance testing and reference software,” in Optics, Photonics and Digital Technologies for Imaging Applications VI 2020, SPIE Press, 2020.

D. M Roijers, L. Zintgraf, P. Libin, M. Reymond, E. Bargiacchi and A. Nowé, “Interactive Multi-Objective Reinforcement Learning in Multi-Armed Bandits with Gaussian Process Utility Models,” in European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020, Springer, 2020, pp. 16.

D. Steckelmacher, H. Plisnier, D. Roijers and A. Nowé, “Sample-Efficient Model-Free Reinforcement Learning with Off-Policy Critics,” in European Conference on Machine Learning 2019, Springer, 2020, pp. 16.

D. Yasuki, D. Blinder, T. Shimobaba, P. Schelkens, T. Kakue and T. Ito, “Hologram calculation in sparse Fourier bases using fixed-point operations, and its circuit architecture,” in SPIE Photonics Europe, 2020, SPIE, Apr. 2020, pp. 13.

F. Nooralahzadeh, G. Bekoulis, J. Bjerva and I. Augenstein, “Zero-Shot Cross-Lingual Transfer with Meta Learning,” in The 2020 Conference on Empirical Methods in Natural Language Processing, Association for Computational Linguistics, Nov. 2020, pp. 16.

F. Van Gestel, T. Frantz, M. Hussain Soomro, S. Elprama, A. Jacobs, J. Vandemeulebroucke, B. Jansen, T. Scheerlinck and J. Duerinck, “AUGMENTED REALITY ASSISTED NEUROSURGICAL DRAIN PLACEMENT (ARANED): TECHNICAL NOTE,”, Mar. 2020.

G. De Oliveira Ramos, R. Radulescu, A. Nowé and A. Tavares, “Toll-Based Learning for Minimising Congestion under Heterogeneous Preferences,” in Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020, Feb. 2020.

H. Van Luong, B. Joseph Joukovsky, Y. Eldar and N. Deligiannis, “A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation,” in 28th European Signal Processing Conference, Oct. 2020, pp. 5.

I. Del Carmen Grau Garcia, D. Sengupta, M. M. Garcia Lorenzo and A. Nowé, “An Interpretable Semi-supervised Classifier using Rough Sets for Amended Self-labeling,” in IEEE World Congress on Computational Intelligence (WCCI) 2020, IEEE, 2020.

I. Del Carmen Grau Garcia, D. Sengupta, M. M. Garcia Lorenzo and A. Nowé, “Extended Abstract: An Interpretable Semi-supervised Classifier using Rough Sets for Amended Self-labeling,” in 32nd Benelux Conference on Artificial Intelligence/Belgian-Dutch Conference on Machine Learning, Leiden, the Netherlands, 2020.

J. Hofman, T. Do, X. Qin, E. Rodrigo, M. Niko-laou, W. Philips, N. Deligiannis and V. Panzica La Manna, “Spatiotemporal Air Quality Inference of Low-Cost Sensor Data Application on a Cycling Monitoring Network,” in Workshop on "Machine Learning Advances Environmental Science (MAES), Nov. 2020, pp. 9.

J. Hofman, M. Nikolaou, T. Do, X. Qin, E. Rodrigo, W. Philips, N. Deligiannis and V. Panzica La Manna, “Mapping Air Quality in IoT Cities: Cloud Calibration and Air Quality Inference of Sensor Data,” in IEEE SENSORS 2020, IEEE, Oct. 2020, pp. 4.

J. Nguyen, K. Khalaf, S. Brebels, M. Shrivas, K. Vaesen and P. Wambacq, “A 10.56Gbit/s, -27.8dB EVM Polar Transmitter at 60GHz in 28nm CMOS,” in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), Jun. 2020.

M. Brandalero, M. Ali, L. Le Jeune, H. Gerardo Muñoz Hernandez, M. Veleski, B. da Silva Gomes, J. Lemeire, K. Van Beeck, A. Touhafi, T. Goedeme, N. Mentens, D. Göhringer and M. Hubner, “AITIA: Embedded AI Techniques for Embedded Industrial Applications,” in 2020 International Conference on Omni-layer Intelligent Systems (COINS), Aug. 2020, pp. 7.

M. Perez Gonzalez, A. Díaz Berenguer, M. Oveneke and H. Sahli, “Neural Architecture Search under black-box objectives with deep reinforcement learning and increasingly-sparse rewards,” in International Conference on Artificial Intelligence in Information and Communication, IEEE, Feb. 2020.

N. Ospitia Patino, A. Pourkazemi, E. Tsangouri, J. Stiens and D. Angelis, “Elastic and ElectroMagnetic Wave monitoring of early age TRC,” in 1st International Electronic Conference on Applied Sciences, MDPI AG, Nov. 2020, pp. 1.

P. Boonen, N. Buls, G. Van Gompel, Y. De Brucker, D. Aerden, L. Tim, J. De Mey and J. Vandemeulebroucke, “Contrast flow velocity quantification from time-resolved CT angiography: a phantom study,” in SPIE Medical Imaging 2020, Mar. 2020.

P. Libin, A. Moonens, T. Verstraeten, F. Ramiro Perez Sanjines, N. Hens, P. Lemey and A. Nowé, “Deep reinforcement learning for large-scale epidemic control,” in Proceedings of the Adaptive and Learning Agents Workshop 2020 (ALA2020) at AAMAS, 2020, pp. 9.

P. Libin, T. Verstraeten, D. Roijers, K. Theys and A. Nowé, “Bayesian Anytime m-top Exploration,” in ICTAI, Feb. 2020, pp. 7.

R. Radulescu, P. Mannion, D. M Roijers and A. Nowé, “Multi-Objective Multi-Agent Decision Making: A Utility-based Analysis and Survey: JAAMAS Track,” in The 19th International Conference on Autonomous Agents and Multi-Agent Systems 2020, IFAAMAS, 2020.

R. Radulescu, P. Mannion, D. M Roijers and A. Nowé, “Recent Advances in Multi-Objective Multi-Agent Decision Making,” in 32nd Benelux Conference on Artificial Intelligence/Belgian-Dutch Conference on Machine Learning, Nov. 2020, pp. 2.

S. Jaxy, I. Del Carmen Grau Garcia, N. Potyka1, G. Pappaert, C. Olsen and A. Nowé, “Thesis Abstract: Teaching a Machine to Diagnose a Heart Disease. Beginning from digitizing scanned ECGs to detecting the Brugada Syndrome (BrS),” in 32nd Benelux Conference on Artificial Intelligence/Belgian-Dutch Conference on Machine Learning, Leiden, The Netherlands, 2020.

T. Verstraeten, E. Bargiacchi, P. Libin, D. M Roijers and A. Nowé, “Thompson Sampling for Factored Multi-Agent Bandits,” in The 19th International Conference on Autonomous Agents and Multi-Agent Systems, IFAAMAS, May. 2020, pp. 2.

T. Verstraeten, E. Bargiacchi, P. Libin, J. Helsen, D. M Roijers and A. Nowé, “Multi-Agent Thompson Sampling for Bandits with Sparse Neighbourhood Structures,” in 32nd Benelux Conference on Artificial Intelligence/Belgian-Dutch Conference on Machine Learning, CEUR Workshop Proceedings, Nov. 2020, pp. 2.

T. Verstraeten, P. Libin and A. Nowé, “Fleet Control using Coregionalized Gaussian Process Policy Iteration,” in the 24th European Conference on Artificial Intelligence (ECAI 2020), Jun. 2020.

V. Putcha, E. Bury, J. Franco, A. Walke, U. Peralagu, A. Alian, B. Kaczer, N. Waldron, D. Linten, B. Parvais and N. Collaert, “Exploring the DC reliability metrics for scaled GaN-on-Si devices targeted for RF/5G applications,” in 2020 IEEE International Reliability Physics Symposium, IRPS 2020, Institute of Electrical and Electronics Engineers Inc, Apr. 2020.

Y. Coppens, D. Steckelmacher, C. M Jonker and A. Nowé, “Synthesising Reinforcement Learning Policies through Set-Valued Inductive Rule Learning,” in Proceedings of the 1st TAILOR workshop at ECAI 2020, Sep. 2020, pp. 16.

Y. Liu, X. Tang, G. Mangraviti, K. Khalaf, y. zhang, w. wu, S. Chen, B. Debaillie and P. Wambacq, “A 28 GHz front-end module with T/R switch achieving 17.2 dBm Psat, 21.5% PAEmax and 3.2 dB NF in 22 nm FD-SOI for 5G communication,” in 2020 IEEE Radio Frequency Integrated Circuits Symposium (RFIC), IEEE, Aug. 2020.

Y. Martinez Jimenez, J. Coto Palacio and A. Nowé, “Multi-Agent Reinforcement Learning Tool for Job Shop Scheduling Problems,” in The International Conference in Optimization and Learning, Springer, 2020, pp. 10.

Y. Zhang, R. Radulescu, P. Mannion, D. M Roijers and A. Nowé, “Opponent Modelling using Policy Reconstruction for Multi-Objective Normal Form Games,” in Proceedings of the Adaptive and Learning Agents Workshop 2020 (ALA2020) at AAMAS, 2020, pp. 9.

Y. Zhang, R. Radulescu, P. Mannion, D. Roijers and A. Nowé, “Opponent Modelling for Reinforcement Learning in Multi-Objective Normal Form Games: Extended Abstract,” in Proceedings of the 19th International Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2020, IFAAMAS, Feb. 2020.

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