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ETRO Publications

All 2020 Publications

All ETRO 2020 Publications by Category

Click here for this list in essential format.

Journal Publications

D. Blinder and P. Schelkens, “Phase added sub-stereograms for accelerating computer generated holography,” Optics Express, vol. 28, no. 11, pp. 16924-16934, May. 2020.

A. Pourkazemi and J. Stiens, “Error Assessment and Mitigation Methods in Transient Radar Method,” Sensors, vol. 20, no. 263, pp. 1-17, Jan. 2020.

G. Jegannathan, H. Ingelberts and M. Kuijk, “Current-Assisted Single Photon Avalanche Diode (CASPAD) Fabricated in 350 nm Conventional CMOS,” Applied Sciences, vol. 10, no. 6, pp. 8, Mar. 2020.

S. Mahmoudpour and P. Schelkens, “Omnidirectional Video Quality Index Accounting for Judder,” IEEE Transactions on Circuits and Systems for Video Technology, pp. 15, Jan. 2020.

T. Birnbaum, “Object-based digital hologram segmentationand motion compensation,” Opt. Express, 2020.

T. Birnbaum, D. Blinder, R. Kizhakkumkara, C. Schretter, A. Symeonidou and P. Schelkens, “Object-based digital hologram segmentation and motion compensation,” Optics Express, vol. 28, no. 8, pp. 11861-11882, Apr. 2020.

S. Patonico, P. Shabisha, A. Braeken, A. Touhafi and K. Steenhaut, “Elliptic curve-based proxy re-signcryption scheme for secure data storage on the cloud,” Concurrency Computation, vol. 2020, Jan. 2020.

P. Hu, N. Nourbakhsh, J. Tian, S. Sturges, V. Dadarlat and A. Munteanu, “A generic method of wearable items virtual try-on,” Textile research journal, Mar. 2020.

X. Tang, J. Nguyen, A. Medra, K. Khalaf, A. Visweswaran, B. Debaillie and P. Wambacq, “Design of D-Band Transformer-Based Gain-Boosting Class-AB Power Amplifiers in Silicon Technologies,” IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 2020, pp. 12, Feb. 2020.

C. Chen, J. Stiens, T. Hauffman, S. Pletincx and R. Inocente Revilla Castillo, “Exploration and mechanism analysis: The maximum ultraviolet luminescence limits of ZnO/few-layer graphene composite films,” Applied Surface Science, vol. 503, pp. 1-9, Feb. 2020.

Y. Yang, S. Song, D. Liu, J. C-W Chan, J. Li and J. Zhang, “Hyperspectral Anomaly Detection through Sparse Representation with Tensor Decomposition-based Dictionary Construction and Adaptive Weighting,” IEEE Access, vol. 8, pp. 72121-72137, 2020.

B. Fang, Y. Li, H. Zhang and J. C-W Chan, “Collaborative learning of lightweight convolutional neural network and deep clustering for hyperspectral image semi-supervised classification with limited training samples,” ISPRS Journal of Photogrammetry and Remote Sensing, vol. 161, pp. 164-178, 2020.

B. Joseph Joukovsky, P. Hu and A. Munteanu, “A Multi-Modal Deep Network for RGB-D Segmentation of Clothes,” Electronics Letters, Jan. 2020.

B. Oniga, L. Denis, V. Dadarlat and A. Munteanu, “Message-Based Communication for Heterogeneous Internet of Things Systems,” Sensors, vol. 20, no. 3, Feb. 2020.

C. Gupta, A. Gupta, S. Tuli, E. Bury, B. Parvais and A. Dixit, “Characterization and Modeling of Hot Carrier Degradation in N-Channel Gate-All-Around Nanowire FETs,” IEEE Transactions on Electron Devices, vol. 67, no. 1, pp. 4-10, Jan. 2020.

C. Yi, Y. Zhao, J. C-W Chan and S. G. Kong, “Joint Spatial-spectral Resolution Enhancement of Multispectral Images with Spectral Matrix Factorization and Spatial Sparsity Constraints,” Remote Sensing, vol. 12, no. 6, 2020.

G. De Oliveira Ramos, B. Castro da Silva, R. Radulescu, A. Bazzan and A. Nowé, “Toll-based reinforcement learning for efficient equilibria in route choice,” The Knowledge Engineering Review, vol. 35, pp. 23, Mar. 2020.

L. Arco Garcia, G. María Casas Cardoso and A. Nowé, “Two-level clustering methodology for smart metering data,” Cuadernos de Administración, 2020.

L. Costers, J. Van Schependom, J. Laton, J. Baijot, M. Sjøgård, V. Wens, X. De Tiège, S. Goldman, M. Dhaeseleer, M. Dhooghe, M. Woolrich and G. Nagels, “Spatiotemporal and spectral dynamics of multi-item working memory as revealed by the n-back task using MEG,” Human Brain Mapping, vol. 41, no. 9, pp. 2431-2446, Jun. 2020.

O. Van Hove, A. Van Muylem, V. Andrianopoulos, D. Leduc, V. Feipel, G. Deboeck and B. Bonnechère, “The use of cognitive mobile games to assess the interaction of cognitive function and breath-hold,” Respiratory Physiology and Neurobiology, vol. 274, no. 103359, pp. 1-6, Mar. 2020.

Q. Liu, L. Xiao, J. Yang and J. C-W Chan, “Content-Guided Convolutional Neural Network for Hyperspectral Image Classification,” IEEE Transactions on Geoscience and Remote Sensing, Mar. 2020.

R. Baes, L. Lemmens, M. Carlier and E. Peeters, “Defining heat shock response for the thermoacidophilic model crenarchaeon Sulfolobus acidocaldarius,” Extremophiles, Jun. 2020.

R. Radulescu, P. Mannion, Y. Zhang, D. Roijers and A. Nowé, “A Utility-Based Analysis of Equilibria in Multi-Objective Normal Form Games,” The Knowledge Engineering Review, Mar. 2020.

R. Willaert, P. Kris Vanden Boer, A. Malovichko, M. Perez Gonzalez, K. Radotic, D. Bartolic, A. Kalauzi, M. Ines Villalba, D. Sanglard, G. Dietler, H. Sahli and S. Kasas, “Single yeast cell nanomotions correlate with cellular activity,” Science Advances, vol. 6, no. 26, pp. 1-8, Jun. 2020.

S. Decavele, E. Ortibus, A. Van Campenhout, G. Molenaers, B. Jansen, L. Omelina and I. Franki, “The effect of a rehabilitation specific gaming software platform to achieve individual physiotherapy goals in children with severe spastic CP: a randomized cross-over trial,” Games For Health Journal, 2020.

T. Verstraeten, E. Bargiacchi, P. Libin, J. Helsen, D. Roijers and A. Nowé, “Multi-Agent Thompson Sampling for Bandit Applications with Sparse Neighborhood Structures,” Scientific Reports - Nature, vol. 10, no. 1, pp. 14, Apr. 2020.

W. Li, Y. Li, W. Darwish, S. Tang, Y. Hu and W. Chen, “A Range-Independent Disparity-Based Calibration Model for Structured Light Pattern-Based RGBD Sensor,” Sensors, vol. 20, no. 3, Jan. 2020.

X. Kong, Y. Zhao, J. Xue, J. C-W Chan and S. G. Kong, “Global and Local Tensor Sparse Approximation Models for Hyperspectral Image Destriping,” Remote Sensing, vol. 12, no. 4, Feb. 2020.

Y. Bu, Y. Zhao, J. Xue, J. C-W Chan, S. G. Kong, C. Yi, J. Wen and B. Wang, “Hyperspectral and Multispectral Image Fusion via Graph Laplacian Guided Coupled Tenor Decomposition,” IEEE Transactions on Geoscience and Remote Sensing, 2020.

Y. Li and J. C-W Chan, “Thick Cloud Removal with Optical and SAR Imagery via Convolutional-Mapping -Deconvolutional Network,” IEEE Transactions on Geoscience and Remote Sensing, vol. 58, no. 4, pp. 2865-2879, Apr. 2020.

Y. Li, W. Li, W. Darwish, S. Tang, Y. Hu and W. Chen, “Improving Plane Fitting Accuracy with Rigorous Error Models of Structured Light-Based RGB-D Sensors,” Remote Sensing, vol. 12, no. 2, Jan. 2020.

Y. Li, W. Li, S. Tang, W. Darwish, Y. Hu and W. Chen, “Automatic Indoor as-Built Building Information Models Generation by Using Low-Cost RGB-D Sensors,” Sensors, vol. 20, no. 1, Jan. 2020.

Conference Publications

&. 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.

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.

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.

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.

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.

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.

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.

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.

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

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. 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.

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.

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.

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. 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, Mar. 2020.

T. Verstraeten, E. Bargiacchi, P. Libin, D. Roijers and A. Nowé, “Thompson Sampling for Factored Multi-Agent Bandits,” in Autonomous Agents and Multi-Agent Systems, May. 2020.

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

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. 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.

Y. Zhang, R. Radulescu, P. Mannion, D. 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, Mar. 2020, pp. 9.

Book Publications

J. Yang, Y. Zhao and J. C-W Chan, “Hyperspectral-Multispectral Image Fusion Enhancement Based on Deep Learning,” in Hyperspectral Image Analysis - Advances in Machine Learning and Signal Processing, Springer, 2020.

Other Publications

J. Van Schependom, K. Guldolf, M. Dhooghe, G. Nagels and M. Dhaeseleer, “Correction to: Detecting neurodegenerative pathology in multiple sclerosis before irreversible brain tissue loss sets in,” Translational neurodegeneration, 2020.

S. Amador Sanchez, J. Dhont, M. Malbrain, J. De Mey and J. Vandemeulebroucke, “Feasibility of virtual dual-energy imaging through deep learning for markerless tumour tracking,”, Jul. 2020.

G. He, C. Chen and J. Stiens, “Reconfigurable Terahertz Dipole Antenna with Integrated Graphene Sheets,”, 2020.

I. Del Carmen Grau Garcia, D. Sengupta, M. M. Garcia and A. Nowé, “An interpretable semi-supervised classifier using two different strategies for amended self-labeling,”, Jan. 2020.

T. Verstraeten, E. Bargiacchi, P. Libin, D. Roijers and A. Nowé, “Thompson Sampling for Loosely-Coupled Multi-Agent Systems: An Application to Wind Farm Control,”, May. 2020.

V. Knoop, A. Costenoble, R. Vella Azzopardi, S. Vermeiren, A. Debain, B. Jansen, A. Scafoglieri and I. Bautmans, “Ratio between muscle fatigability and self-perceived tiredness could be an important parameter for characterizing frailty,”, Feb. 2020.

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