Publications

Friðriksdóttir, Steinunn Rut; Einarsson, Hafsteinn (2022): Friðriksdóttir & Einarsson (2022), Bootstrapping Icelandic Knowledge Graph Data. University of Amsterdam / Amsterdam University of Applied Sciences. Conference contribution. https://doi.org/10.21942/uva.20367948.v1

Snæbjarnarson, V., & Einarsson, H. (2022, July). Cross-Lingual QA as a Stepping Stone for Monolingual Open QA in Icelandic. In Proceedings of the Workshop on Multilingual Information Access (MIA) (pp. 29-36).

Snæbjarnarson, V., & Einarsson, H. (2022, June). Natural questions in icelandic. In Proceedings of the Thirteenth Language Resources and Evaluation Conference (pp. 4488-4496).

Friðriksdóttir, S. R., Eggertsson, V. Á., Jóhannesson, B. G., Daníelsson, H., Loftsson, H., & Einarsson, H. (2022, June). Building an Icelandic Entity Linking Corpus. In Proceedings of the Workshop on Dataset Creation for Lower-Resourced Languages within the 13th Language Resources and Evaluation Conference (pp. 27-35).

Friðriksdóttir, S. R., & Einarsson, H. (2022, June). Fictionary-Based Games for Language Resource Creation. In Proceedings of the 2nd Workshop on Novel Incentives in Data Collection from People: models, implementations, challenges and results within LREC 2022 (pp. 25-31).

Snæbjarnarson, V., Símonarson, H. B., Ragnarsson, P. O., Ingólfsdóttir, S. L., Jónsson, H., Þorsteinsson, V., & Einarsson, H. (2022, June). A Warm Start and a Clean Crawled Corpus-A Recipe for Good Language Models. In Proceedings of the Thirteenth Language Resources and Evaluation Conference (pp. 4356-4366).

H. Myneni, E.O. Jónsson, H. Jónsson*, and A.O. Dohn*, Polarizable force field for acetonitrile based on the single-center multipole expansion, The Journal of Physical Chemistry B 126, 9339 (2022); https://doi.org/10.1021/acs.jpcb.2c04255

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K. Trepte, S. Schwalbe, S. Liebing, W.T. Schulze, J. Kortus, H. Myneni, A.V. Ivanov, and S. Lehtola, Chemical bonding theories as guides for self-interaction corrected solutions: multiple local minima and symmetry breaking, The Journal of Chemical Physics 155, 224109 (2021); https://doi.org/10.1063/5.0071796

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S. Jana, H. Myneni, S. Śmiga, L.A. Constantin, and P. Samal, Benchmark test of a dispersion corrected revised Tao–Mo semilocal functional for thermochemistry, kinetics, and noncovalent interactions of molecules and solids, The Journal of Chemical Physics155, 114102 (2021); https://doi.org/10.1063/5.0060538

C. Shahi, P. Bhattarai, K. Wagle, B. Santra, S. Schwalbe, T. Hahn, J. Kortus, K.A. Jackson, J.E. Peralta, K. Trepte, S. Lehtola, N.K. Nepal, H. Myneni, B. Neupane, S. Adhikari, A. Ruzsinszky, Y. Yamamoto, T. Baruah, R.R. Zope, and J.P. Perdew, Stretched or noded orbital densities and self-interaction correction in density functional theory, The Journal of Chemical Physics 150, 174102 (2019); https://doi.org/10.1063/1.5087065

S. Jana, A. Patra, L.A. Constantin, H. Myneni, and P. Samal, Long-range screened hybrid functional theory satisfying the local density linear response, Physical Review A 99, 042515 (2019); https://doi.org/10.1103/PhysRevA.99.042515

S. Jana, B. Patra, H. Myneni, and P. Samal, On the many-electron self-interaction error of the semilocal exchange hole based meta-GGA level range-separated hybrid with the B88 hybrids, Chemical Physics Letters 713, 1 (2018); https://doi.org/10.1016/j.cplett.2018.10.007

A. Patra, S. Jana, H. Myneni, and P. Samal, Laplacian free and asymptotic corrected semilocal exchange potential applied to the band gap of solids, Physical Chemistry Chemical Physics 21, 19639 (2019); https://doi.org/10.1039/C9CP03356D

H. Myneni and M.E. Casida, On the calculation of ∆<Ŝ^2>_i for electronic excitations in time-dependent density-functional theory, Computer Physics Communications 213, 72 (2017); http://dx.doi.org/10.1016/j.cpc.2016.12.011

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P. Singh, M.K. Harbola, M. Hemanadhan (H. Myneni), A. Mookerjee, and D.D. Johnson, Better band gaps with asymptotically corrected local exchange potentials, Physical Review B 93, 085204 (2016); http://dx.doi.org/10.1103/PhysRevB.93.085204

H. Myneni, D. Kedziera, J.W. Andzelm, J. Austad, E.I. Tellgren, T. Helgaker, and K. Szalewicz, Effects of strong magnetic fields on water from rigorous quantum calculations (Manuscript: https://www.dropbox.com/s/it6r1cbx8b1k3et/Hemanadhan_Krzysztof_Water1.pdf?dl=0)

Elvar Atli Ævarsson, Thórhildur Ásgeirsdóttir, Finnur Pind, Árni Kristjánsson, and Runar Unnthorsson. 2022. Vibrotactile Threshold Measurements at the Wrist Using Parallel Vibration Actuators. ACM Trans. Appl. Percept. 19, 3, Article 10 (July 2022), 11 pages. https://doi.org/10.1145/3529259

Hoffmann, R., Brinkhuis M.A.B., Unnthorsson, Runar, Kristjansson, Arni, The Intensity Order Illusion: Temporal Order of Different Vibrotactile Intensity Causes Systematic Localization Error, Journal of Neurophysiology, Volume 122, Issue 4, October 2019, Pages 1810-1820, https://doi.org/10.1152/jn.00125.2019

Spagnol, Simone; Purkhús, Kristján Bjarki; Unnthorsson, Rúnar; Björnsson, Sverrir Karl.The Viking HRTF dataset (2019) Proceedings of the Sound and Music Computing Conferences, pp. 55 – 60, https://www.scopus.com/record/display.uri?eid=2-s2.0-85084386330&origin=inward

S.Spagnol, K. B. Purkhús, S. K. Björnsson and R. Unnthórsson – A head-related transfer function dataset of KEMAR with various pinna shapes, XXII Colloquium of Musical Informatics Udine, November 20-23, 2018

Hoffmann, Rebekka; Spagnol, Simone; Kristjánsson, Árni; Unnthorsson, Runar. Evaluation of an Audio-haptic Sensory Substitution Device for Enhancing Spatial Awareness for the Visually Impaired, Optometry and Vision Science: September 2018 – Volume 95 – Issue 9 – p 757–765

Simone Spagnol, Rebekka Hoffmann, Marcelo Herrera Martínez, Runar Unnthorsson, Blind wayfinding with physically-based liquid sounds, International Journal of Human-Computer Studies,Volume 115, Pages 9-19, 2018

Serafin, Stefania; Dahl, Sofia; Bresin, Roberto; Jensenius, Alexander Refsum; Unnthorsson, Runar; Välimäki, Vesa. NordicSMC: A nordic university hub on sound and music computing. (2018) Proceedings of the 15th Sound and Music Computing Conference: Sonic Crossings, SMC 2018, pp. 124 – 128, https://www.scopus.com/record/display.uri?eid=2-s2.0-85075104318&origin=inward

P. Strumillo, M. Bujacz, P. Baranski, P. Skulimowski, P. Korbel, M. Owczarek, K. Tomalczyk, A. Moldoveanu & R. Unnthorsson. (2018). Different Approaches to Aiding Blind Persons in Mobility and Navigation in the “Naviton” and “Sound of Vision” Projects. In: Pissaloux, E., Velazquez, R. (eds) Mobility of Visually Impaired People. Springer, Cham. https://doi.org/10.1007/978-3-319-54446-5_15

Simone Spagnol, György Wersényi, Michal Bujacz,Oana Bălan, Marcelo Herrera Martínez, Alin Moldoveanu and Runar Unnthorsson, Current Use and Future Perspectives of Spatial Audio Technologies in Electronic Travel Aids, Wireless Communications and Mobile Computing, vol. 2018 doi:10.1155/2018/3918284

Hoffmann, R., Valgeirsdóttir, V.V., Jóhannesson, Ó.I., Kristjansson, Arni, Runar Unnthorsson, Measuring relative vibrotactile spatial acuity: effects of tactor type, anchor points and tactile anisotropy, Exp Brain Res (2018). https://doi.org/10.1007/s00221-018-5387-z

Hoffmann R., Brinkhuis M., Kristjánsson Á. and Unnthorsson R. (2018). Introducing a New Haptic Illusion to Increase the Perceived Resolution of Tactile Displays.In Proceedings of the 2nd International Conference on Computer-Human Interaction Research and Applications – Volume 1: CHIRA, ISBN 978-989-758-328-5, pages 45-53. DOI: 10.5220/0006899700450053

S. Spagnol, S. Baldan, and R. Unnthorsson. Auditory depth map representations with a sensory substitution scheme based on synthetic fluid sounds. In Proc. IEEE Int. Workshop on Multimedia Signal Processing (MMSP 2017), Luton, October 2017.

A. Csapo, S. Spagnol, M. Herrera Martinez, M. Bujacz, M. Janeczek, G. Ivanica, G. Wersenyi, A. Moldoveanu, and R. Unnthorsson. Usability and effectiveness of auditory sensory substitution models for the visually impaired. In Proc. 142nd Conv. Audio Engineering Society, May 2017.

Bălan, Oana; Moldoveanu, Alin; Moldoveanu, Florica; Nagy, Hunor;Wersényi, György; Unnþórsson, Rúnar. Improving the audio game–playing performances of people with visual impairments through multimodal training (2017) Journal of Visual Impairment and Blindness, 111 (2), pp. 148 – 164, https://doi.org/10.1177/0145482x1711100206

Johannesson, Omar I.; Hoffmann, Rebekka; Valgeirsdottir, Vigdis Vala; Unnthorsson, Runar; Moldoveanu, Alin; Kristjansson, Arni, Relative vibrotactile spatial acuity of the torso, EXPERIMENTAL BRAIN RESEARCH Volume: 235 Issue: 11 Pages: 3505-3515, 2017

Alin Moldoveanu, Oana Balan, Maria-Iuliana Dascalu, Iulia Stanica, Constanta-Nicoleta Bodea, Rúnar Unnþórsson, Florica Moldoveanu (2017). Sound Of Vision 3d Virtual Training Environments – A Gamification Approach For Visual To Audio-Haptic Sensory Substitution. Revue Roumaine des Sciences Techniques-Serie Electrotechnique et Energetique, Issue: 1 | Pp.: 112-117,2018, Romanian Academy, Publishing House of the Romanian Academy,ISSN: 0035- 4066

Spagnol, S.; Saitis, C.; Bujacz, M.; Jóhannesson, Ó. I.; Kalimeri, K.; Moldoveanu, A.; Kristjánsson, Á. & Unnthorsson, R. Model-Based Obstacle Sonification for the Navigation of Visually Impaired Persons. Proc. 19th Int. Conf. Digital Audio Effects (DAFx-16), Czech Republic, September 2016.

M. Bujacz, K. Kropidlowski, G. Ivanica, A. Moldoveanu, C. Saitis, A. Csapo, G. Wersenyi, S. Spagnol, O. Johannesson, R. Unnthorsson, M. Rotnicki, and P. Witek.Sound of Vision – Spatial audio output and sonification approaches. Chapter in Computers Helping People with Special Needs, edited by K. Miesenberger, C. Buehler, and P. Penaz, pages 202-209, Springer, July 2016

Kristjánsson Á, Moldoveanu A, Jóhannesson ÓI, Balan O, Spagnol S, Valgeirsdóttir VV, Unnthorsson R. (2016). Designing sensory-substitution devices: Principles, pitfalls and potential1. Restorative neurology and neuroscience, 34(5), 769-787

Ómar I Jóhannesson, Oana Balan, Runar Unnthorsson, Alin Moldoveanu, Árni Kristjánsson, The Sound of Vision Project: On the Feasibility of an Audio-Haptic Representation of the Environment, for the Visually Impaired, Brain Sci. 2016, 6(3), 20; doi:10.3390/brainsci6030020

Hassanian, R., Myneni, H., Helgadóttir, Á. & Riedel, M. Deciphering the dynamics of distorted turbulent flows: Lagrangian particle tracking and chaos prediction through transformer-based deep learning models, 1 July. 2023, Í: Physics of Fluids. 35, 7, 075118.

Hassanian, R., Helgadóttir, Á. & Riedel, M. A wake loss model asymmetry induced by the circulation of a vertical axis wind turbine, 12 June. 2023, 2023 International Conference on Future Energy Solutions, FES 2023. Institute of Electrical and Electronics Engineers Inc., (2023 International Conference on Future Energy Solutions, FES 2023).

Hassanian, R., Helgadóttir, Á. & Riedel, M. Iceland Wind Farm Assessment Case Study and Development: An Empirical Data from Wind and Wind Turbine, 1 April. 2023, Í: Cleaner Energy Systems. 4C

Hassanian, R., Yeganeh, N., Helgadóttir, Á. & Riedel, M. A Novel Implicit Model Determines the Photovoltaic Panel Temperature and Environmental Effects, 5 March. 2023, APS March Meeting 2023.

Hassanian, R., Helgadóttir, Bouhlali, L. & Riedel, M. An experiment generates a specified mean strained rate turbulent flow: Dynamics of particles, jan. 2023, Í: Physics of Fluids. 35, 1, 015124.

Hassanian, R., Helgadóttir, Á. & Riedel, M. Deep Learning Forecasts a Strained Turbulent Flow Velocity Field in Temporal Lagrangian Framework: Comparison of LSTM and GRU: Comparison of LSTM and GRU, 3 November. 2022, Í: Fluids. 7, 11, 344.

R Hassanian, M Riedel, “Mechanical Elements Analysis of Stewart Platform: Computational Approach”, International Journal of Science and Research (IJSR) 11 (4),  2022, pp. 1166 – 1171, Online: https://hdl.handle.net/20.500.11815/3313

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Hassanian, R., Riedel, M., Helgadottir, A., Yeganeh, N. & Unnthorsson, R. Implicit Equation for Photovoltaic Module Temperature and Efficiency via Heat Transfer Computational Model, 21 February. 2022, Í: Thermo.

R. Hassanian, M. Riedel, P. Costa, A. Helgadottir, L. Bouhlali, “Lagrangian Particle Tracking Data of a Straining Turbulent Flow Assessed Using Machine Learning and Parallel Computing,” in Proceedings of 33rd Parallel Computational Fluid Dynamics (ParCFD) 2022. Alba, Italy, 2022, Online: https://hdl.handle.net/20.500.11815/3515

Hassanian, R., Riedel, M., Yeganeh, N., Unnthorsson, R.: A Practical Approach for Estimating the Optimum Tilt Angle of a Photovoltaic Panel for a Long Period—Experimental Recorded Data, Journal of MDPI Solar, vol. 1, no 1, 2021

Z. Ahmed, D. Izbassarov, P. Costa, M. Muradoglu, and O. Tammisola. Turbulent bubbly channel flows: Effects of soluble surfactant and viscoelasticity. Comput. Fluids : 104717 (2020)

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N. Scapin, P. Costa, and L. Brandt. A volume-of-fluid method for interface-resolved simulations of phase-changing two-fluid flowsJ. Comput. Phys. 407 : 109251 (2020)

P. Costa, L. Brandt, and F. Picano. Interface-resolved simulations of small inertial particles in turbulent channel flow. J. Fluid Mech. 883 : A54 (2020)

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B. Indurain, D. Uystepruyst, F. Beaubert, S. Lalot, Á. Helgadóttir. Numerical investigation of several twisted tubes with non-conventional tube cross sections on heat transfer and pressure drop. Journal of Thermal Analysis and Calorimetry. 140: 1555-1568 (2020). https://doi.org/10.1007/s10973-019-08965-4

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Á. Helgadóttir, A. Guittet, F. Gibou. On Solving the Poisson Equation with Discontinuities on Irregular Interfaces: GFM and VIM. International Journal of Differential Equations. 2018: Article ID 9216703 (2018). https://doi.org/10.1155/2018/9216703

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Á. Helgadóttir, Y.-T. Ng, C. Min, F. Gibou. Imposing Mixed Dirichlet-Neumann-Robin Boundary Conditions in a Level-Set Framework. Computers and Fluids. 121: 68-80 (2015). https://doi.org/10.1016/j.compfluid.2015.08.007

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P. Costa. A FFT-based finite-difference solver for massively-parallel direct numerical simulations of turbulent flows. Comput. Math. Appl. 76 : 1853 – 1862 (2018)

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Á. Helgadóttir, S. Lalot, F. Beaubert, H. Pálsson. Mesh Twisting Technique for Swirl Induced Laminar Flow Used to Determine a Desired Blade Shape. Applied Sciences. 8 (10): 1865 (2018). https://doi.org/10.3390/app8101865

P. Costa, F. Picano, L. Brandt, and W.-P. Breugem. Universal Scaling Laws for Dense Particle Suspensions in Turbulent Wall-Bounded Flows. Phys. Rev. Lett. 117 (13) : 134501 (2016)

M. Mirzadeh, M. Theillard, Á. Helgadóttir, D. Boy, F. Gibou. An Adaptive, Finite Difference Solver for the Nonlinear Poisson-Boltzmann Equation with Applications to Biomolecular Computations. Communications in Computational Physics. 13 (1): 150-173 (2013). https://doi.org/10.4208/cicp.290711.181011s

J. Papac. Á. Helgadóttir, C. Ratsch, F. Gibou. A level set approach for diffusion and Stefan-type problems with Robin boundary conditions on quadtree/octree adaptive Cartesian grids.Journal of Computational Physics. 233: 241-261 (2013). https://doi.org/10.1016/j.jcp.2012.08.038

Á. Helgadóttir, F. Gibou. A Poisson-Boltzmann solver on Irregular Domains with Neumann or Robin boundary conditions on Non-Graded Adaptive Grid. Journal of Computational Physics. 230 (10): 3830-3848 (2011). https://doi.org/10.1016/j.jcp.2011.02.010

Controlling the excitation spectrum of a quantum dot array with a photoncavity, Vidar Gudmundsson, Vram Mughnetsyan, Nzar Rauf Abdullah, Chi-Shung Tang,Valeriu Moldoveanu, and Andrei Manolescu, Phys. Rev. B 108, 115306 (2023), https://doi.org/10.1103/PhysRevB.108.115306, (arXiv:2305.11544)

Role of planar buckling on the electronic, thermal, and optical properties of Germagraphene nanosheets, Nzar Rauf Abdullah, Yousif Hussein Azeez, Botan Jawdat Abdullah, Hunar Omar Rashid, Andrei Manolescu, and Vidar Gudmundsson, Materials Science in Semiconductor Processing 153, 107163 (2023), https://doi.org/10.1016/j.mssp.2022.107163, (arXiv:2210.04247)

Effects of a far-infrared photon cavity field on the magnetization of a square quantum dot array, Vidar Gudmundsson, Vram Mughnetsyan, Nzar Rauf Abdullah, Chi-Shung Tang, Valeriu Moldoveanu, and Andrei Manolescu, Phys. Rev. B 106, 115308 (2022), https://doi.org/10.1103/PhysRevB.106.115308, (arXiv:2203.11029)

Unified approach to cyclotron and plasmon resonances in a periodic two-dimensional GaAs electron gas hosting the Hofstadter butterfly, Vidar Gudmundsson, Vram Mughnetsyan, Nzar Rauf Abdullah, Chi-Shung Tang, Valeriu Moldoveanu, and Andrei Manolescu, Phys. Rev. B 105, 155302 (2022), https://doi.org/10.1103/PhysRevB.105.155302, (arXiv:2112.08216)

Electroluminescence caused by the transport of interacting electrons through parallel quantum dots in a photon cavity, Vidar Gudmundsson, Nzar Rauf Abdullah, Anna Sitek, Hsi-Sheng Goan, Chi-Shung Tang, and Andrei Manolescu, Annalen der Physik 530, 1700334 (2018), https://doi.org/10.1002/andp.201700334, (arXiv:1706.03483)

C. S. Barakat et al., ‘Developing an Artificial Intelligence-Based Representation of a Virtual Patient Model for Real-Time Diagnosis of Acute Respiratory Distress Syndrome’, Diagnostics, vol. 13, no. 12, p. 2098, Jun. 2023, doi: 10.3390/diagnostics13122098.

M. Riedel et al., ‘Enabling Hyperparameter-Tuning of AI Models for Healthcare using the CoE RAISE Unique AI Framework for HPC’, in 2023 46th MIPRO ICT and Electronics Convention (MIPRO), Opatija, Croatia: IEEE, May 2023, pp. 435–440. doi: 10.23919/MIPRO57284.2023.10159755.

C. Barakat, M. Aach, A. Schuppert, S. Brynjólfsson, S. Fritsch, and M. Riedel, ‘Analysis of Chest X-ray for COVID-19 Diagnosis as a Use Case for an HPC-Enabled Data Analysis and Machine Learning Platform for Medical Diagnosis Support’, Diagnostics, vol. 13, no. 3, 2023, doi: 10.3390/diagnostics13030391.

C. Barakat et al., “Lessons learned on using High-Performance Computing and Data Science Methods towards understanding the Acute Respiratory Distress Syndrome (ARDS),” MIPRO 2022, pp. 368-373, Online: https://doi.org/10.23919/MIPRO55190.2022.9803320

C. Barakat, S. Fritsch, M. Riedel, and S. Brynjolfsson, ‘An HPC-Driven Data Science Platform to Speed-up Time Series Data Analysis of Patients with the Acute Respiratory Distress Syndrome’, in 2021 44th International Convention on Information, Communication and Electronic Technology (MIPRO), Opatija, Croatia: IEEE, Sep. 2021, pp. 311–316. doi: 10.23919/MIPRO52101.2021.9596840.

Yeganeh, N., Makarov, I., Unnthorsson, R., & Kristjánsson, Á. (2026). Assessing Spatial and Spatiotemporal Tactile Working Memory Using Adaptive Staircase Procedures. Sensors, 26(8), 2361. DOI: 10.3390/s26082361

Kristjánsson, Á., Makarov, I., Yeganeh, N., & Unnthorsson, R. (2026). Sensory Substitution Through Vibrotactile Stimulation. In Mobility of Visually Impaired People. Springer. DOI: 10.1007/978-3-031-91550-5_8

Yeganeh, N., Makarov, I., Kristjánsson, Á., & Unnthorsson, R. (2025). Vibrotactile Pattern Recognition: Influence of Interstimulus Intervals. Virtual Reality & Intelligent Hardware, 7(5), 483–500. DOI: 10.1016/j.vrih.2025.06.001

Karimi, M., Yeganeh, N., Makarov, I., et al. (2025). Haptic Feedback Systems for Lower-Limb Prosthetic Applications: A Review of System Design, User Experience, and Clinical Insights. Bioengineering, 12(9), 989. DOI: 10.3390/bioengineering12090989

Yeganeh, N., Makarov, I., Kristjánsson, Á., & Unnthorsson, R. (2024). Discrimination Accuracy of Sequential Versus Simultaneous Vibrotactile Stimulation on the Forearm. Applied Sciences, 14(1), 43. DOI: 10.3390/app14010043

Makarov, I., Stefánsson Thors, S. S., Ævarsson, E. A., Jörgensson, F. K. P., Yeganeh, N., Kristjánsson, Á., & Unnthorsson, R. (2023). Amplitude Changes Cause the Haptic Intensity Order Illusion. ACM Transactions on Applied Perception, 21(1), Article 4. DOI: 10.1145/3626237

Yeganeh, N., Makarov, I., Kristjánsson, Á., & Unnthorsson, R. (2023). Discrimination of Vibrotactile Stimuli: Effects of Frequency Variation. Proceedings of ASME IMECE 2023. DOI: 10.1115/IMECE2023-112457

Yeganeh, N., Makarov, I., Unnthorsson, R., & Kristjánsson, Á. (2023). Effects of Stimulus Frequency and Location on Vibrotactile Discrimination Performance Using Voice Coil Actuators on the Forearm. Actuators, 12(6), 224. DOI: 10.3390/act12060224

Yeganeh, N., Makarov, I., Stefánsson Thors, S. S., Kristjánsson, Á., & Unnthorsson, R. (2023). Evaluating the Optimum Distance Between Voice Coil Actuators Using the Relative Point Localization Method on the Forearm. Actuators, 12(1), 6. DOI: 10.3390/act12010006

Yeganeh, N., Makarov, I., Stefánsson Thors, S. S., Ásgeirsson, H., Kristjánsson, Á., & Unnthorsson, R. (2022). Vibrotactile Sleeve to Improve Music Enjoyment of Cochlear Implant Users. Proceedings of ASME IMECE 2022. DOI: 10.1115/IMECE2022-95591

A. Delilbasic, B. Le Saux, M. Riedel, K. Michielsen, G. Cavallaro, "A Single-Step Multiclass SVM based on Quantum Annealing for Remote Sensing Data Classification," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 17, pp. 1434-1445, 2024, https://doi.org/10.1109/JSTARS.2023.3336926

E. Pasetto, M. Riedel, K. Michielsen, G. Cavallaro, "Kernel Approximation on a Quantum Annealer for Remote Sensing Regression Tasks", in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 17, pp. 3262-3269, 2024, https://doi.org/10.1109/JSTARS.2024.3350385

S. Sharma, R. Sedona, M. Riedel, G. Cavallaro, C. Paris, "Sen4Map: Advancing Mapping with Sentinel-2 by Providing Detailed Semantic Descriptions and Customizable Land-Use and Land-Cover Data," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 17, pp. 13893-13907, 2024, https://doi.org/10.1109/JSTARS.2024.3435081

E. Zardini, A. Delilbasic, E. Blanzieri, G. Cavallaro, D. Pastorello, "Local Binary and Multiclass SVMs Trained on a Quantum Annealer," in IEEE Transactions on Quantum Engineering (TQE), pp. 1-13, 2024, https://doi.org/10.1109/TQE.2024.3475875

J. A. Xavier, J. P. G. Hermosillo Muriedas, S. Nassyr, R. Sedona, M. Götz, A. Streit, M. Riedel, and G. Cavallaro, “Vectorized Highly Parallel Density-Based Clustering for Applications With Noise,” in IEEE Access, vol. 12, pp. 181679–181692, 2024, https://doi.org/10.1109/ACCESS.2024.3507193

A. Farshian, M. Götz, G. Cavallaro, C. Debus, M. Nießner, J. A. Benediktsson, A. Streit, "Deep-Learning-Based 3-D Surface Reconstruction - A Survey," in Proceedings of the IEEE, vol. 111, no. 11, pp. 1464-1501, 2023, https://doi.org/10.1109/JPROC.2023.3321433

S. Moreno-Álvarez, M. E. Paoletti, G. Cavallaro and J. M. Haut, "Enhancing Distributed Neural Network Training Through Node-Based Communications," in IEEE Transactions on Neural Networks and Learning Systems, 2023, https://doi.org/10.1109/TNNLS.2023.3309735

R. Sedona, C. Paris, J. Ebert, M. Riedel and G. Cavallaro, "Toward the Production of Spatiotemporally Consistent Annual Land Cover Maps Using Sentinel-2 Time Series," in IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1-5, no. 2505805, 2023, https://doi.org/10.1109/LGRS.2023.3329428

B. Zhao, H. I. Ragnarsson, M. O. Ulfarsson, G. Cavallaro and J. A. Benediktsson, "Predicting Classification Performance for Benchmark Hyperspectral Datasets," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 15, pp. 4180-4193, 2022, https://doi.org/10.1109/JSTARS.2022.3173893

S. Moreno-Álvarez, M. E. Paoletti, G. Cavallaro, J. A. Rico and J. M. Haut, "Remote Sensing Image Classification Using CNNs With Balanced Gradient for Distributed Heterogeneous Computing," in IEEE Geoscience and Remote Sensing Letters (GRSL), no. 3512205, vol. 19, pp. 1-5, 2022, https://doi.org/10.1109/LGRS.2022.3173052

E. Pasetto, M. Riedel, F. Melgani, K. Michielsen and G. Cavallaro, "Quantum SVR for Chlorophyll Concentration Estimation in Water With Remote Sensing," in IEEE Geoscience and Remote Sensing Letters (GRSL), vol. 19, pp. 1-5, 2022, https://doi.org/10.1109/LGRS.2022.3200325

Y. Bazi, G. Cavallaro, B. Demir, F. Melgani, "Learning from Data for Remote Sensing Image Analysis", in International Journal of Remote Sensing (IJRS), vol. 43, no. 15-16, pp. 5527-5533, 2022, https://doi.org/10.1080/01431161.2022.2131481

R. Sedona, C. Paris, G. Cavallaro, L. Bruzzone, and M. Riedel, “A High-Performance Multispectral Adaptation GAN for Harmonizing Dense Time Series of Landsat-8 and Sentinel-2 Images,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), vol. 14, pp. 10134–10146, 2021, https://doi.org/10.1109/JSTARS.2021.3115604

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R. Sedona, L Hoffmann, R. Spang, G. Cavallaro, S. Griessbach, M. Höpfner, M., Book, M. Riedel, "Exploration of Machine Learning Methods for the Classification of Infrared Limb Spectra of Polar Stratospheric Clouds", in Atmospheric Measurement Techniques, vol 13, no. 7, pp. 3661–3682, 2020, https://doi.org/10.5194/amt-13-3661-2020

R. Sedona, G. Cavallaro, J. Jitsev, A. Strube, M. Riedel, and J. A. Benediktsson, ”Remote Sensing Big Data Classification with High Performance Distributed Deep Learning”, Remote Sensing, vol. 11, no. 24, pp. 3056, 2019.

J. M. Haut, J. A. Gallardo, M. E. Paoletti, G. Cavallaro, J.Plaza, A. Plaza and M. Riedel, "Cloud Deep Networks for Hyperspectral ImageAnalysis," in IEEE Transactions on Geoscience and Remote Sensing (TGRS), vol. 57, no. 12, pp.9832-9848, 2019, https://doi.org/10.1109/TGRS.2019.2929731

M. Goetz, G. Cavallaro, T. Geraud, M. Book, and M. Riedel, ”Parallel Computation of Component Trees on Distributed Memory Machines“, IEEE Transactions on Parallel and Distributed Systems, vol. 29, no. 11, pp. 2582-2598, 2018.

G. Cavallaro, M. Riedel, M. Richerzhagen, J. A. Benediktsson, and A. Plaza, ”On Understanding Big Data Impacts in Remotely Sensed Image Classification Using Support Vector Machine Methods,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS), vol. 8, no. 10, pp. 4634-4646, 2015.

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