CST's 50 Most Recent Publications
T. Lindeberg, "Scale selection," in Computer Vision, 2nd ed. : Springer, 2021.
X. Aguilar, "Performance Monitoring, Analysis, and Real-Time Introspection on Large-Scale Parallel Systems," Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2020:1, 2020.
O. O. Özcan et al., "Differential Coding Strategies in Glutamatergic and GABAergic Neurons in the Medial Cerebellar Nucleus," Journal of Neuroscience, vol. 40, no. 1, pp. 159-170, 2020.
L. Finnveden, Y. Jansson and T. Lindeberg, "The problems with using STNs to align CNN feature maps," in Northern Lights Deep Learning Workshop 2020, Tromsø, Norway, 20-21 Jan 2020, 2020.
K. Dembrower et al., "Comparison of a deep learning risk score and standard mammographic density score for breast cancer risk prediction," Radiology, vol. 294, no. 2, pp. 265-272, 2020.
E. Brocke, "Method development for co-simulation of electrical-chemical systems in Neuroscience," Doctoral thesis : KTH Royal Institute of Technology, TRITA-EECS-AVL, 2020:9, 2020.
T. Lindeberg, "Provably scale-covariant continuous hierarchical networks based on scale-normalized differential expressions coupled in cascade," Journal of Mathematical Imaging and Vision, vol. 62, no. 1, pp. 120-148, 2020.
C. Lacoux et al., "Dynamic insights on transcription initiation and RNA processing during bacterial adaptation," RNA : A publication of the RNA Society, vol. 26, no. 4, pp. 382-395, 2020.
A. Divin et al., "A Fully Kinetic Perspective of Electron Acceleration around a Weakly Outgassing Comet," Astrophysical Journal Letters, vol. 889, no. 2, 2020.
T. Stojanovski, "Urban Mobility Certificates (UMCs) : Informing mobility choices, carbon emissionsand energy use from transportation," Stockholm : KTH Royal Institute of Technology, TRITA-ABE-RPT, 2011, 2020.
J. Bahuguna, A. Sahasranamam and A. Kumar, "Uncoupling the roles of firing rates and spike bursts in shaping the STN-GPe beta band oscillations," PloS Computational Biology, vol. 16, no. 3, 2020.
L. Hunger, A. Kumar and R. Schmidt, "Abundance Compensates Kinetics : Similar Effect of Dopamine Signals on D1 and D2 Receptor Populations," Journal of Neuroscience, vol. 40, no. 14, pp. 2868-2881, 2020.
Y. Jansson et al., "Inability of spatial transformations of CNN feature maps to support invariant recognition," , 2020.
E. Aurell, B. Donvil and K. Mallick, "Large deviations and fluctuation theorem for the quantum heat current in the spin-boson model," Physical review. E, vol. 101, no. 5, 2020.
H.-L. Zeng and E. Aurell, "Inferring genetic fitness from genomic data," Physical Review E. Statistical, Nonlinear, and Soft Matter Physics, vol. 101, no. 5, 2020.
I. Youssef et al., "A Neuro-Inspired Computational Model for a Visually Guided Robotic Lamprey Using Frame and Event Based Cameras," IEEE Robotics and Automation Letters, vol. 5, no. 2, pp. 2395-2402, 2020.
N. Calvo et al., "Can a social robot be persuasive without losing children's trust?," in Companion of the 2020 ACM/IEEE International Conference on Human-Robot Interaction, HRI 2020, 2020, pp. 157-159.
J. J. J. Hjorth et al., "The microcircuits of striatum in silico," Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 17, pp. 9554-9565, 2020.
H. Pierre et al., "Fluid and kinetic modelling of the magnetized Kelvin-Helmholtz instability," in ETC 2013 - 14th European Turbulence Conference, 2020.
Y. Jansson and T. Lindeberg, "Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges," (Manuscript).
L. Finnveden, Y. Jansson and T. Lindeberg, "Understanding when spatial transformer networks do not support invariance, and what to do about it," (Manuscript).
J. H. Spühler et al., "A High Performance Computing Framework for Finite Element Simulation of Blood Flow in the Left Ventricle of the Human Heart," in Lecture Notes in Computational Science and Engineering, 2020, pp. 155-164.
W. Der Chien, I. B. Peng and S. Markidis, "Posit NPB : Assessing the precision improvement in HPC scientific applications," in Lecture Notes in Computer Science, 2020, pp. 301-310.
E. Aurell, R. Kawai and K. Goyal, "An operator derivation of the Feynman-Vernon theory, with applications to the generating function of bath energy changes and to an-harmonic baths," Journal of Physics A : Mathematical and Theoretical, vol. 53, no. 27, 2020.
V. Menon et al., "Microstructural organization of human insula is linked to its macrofunctional circuitry and predicts cognitive control," eLife, vol. 9, 2020.
Y. Jansson and T. Lindeberg, "MNISTLargeScale dataset," , 2020.
G. Chen et al., "Event-Based Neuromorphic Vision for Autonomous Driving : A Paradigm Shift for Bio-Inspired Visual Sensing and Perception," IEEE signal processing magazine (Print), vol. 37, no. 4, pp. 34-49, 2020.
Y. Jansson and T. Lindeberg, "Exploring the ability of CNNs to generalise to previously unseen scales over wide scale ranges," in ICPR2020 25th International Conference on Pattern Recognition, Milan, Italy, January 10-15, 2021, 2020.
A. Solomonidou et al., "Spectral and emissivity analysis of the raised ramparts around Titan's northern lakes," Icarus (New York, N.Y. 1962), vol. 344, 2020.
G. Chen et al., "A Novel Visible Light Positioning System With Event-Based Neuromorphic Vision Sensor," IEEE Sensors Journal, vol. 20, no. 17, pp. 10211-10219, 2020.
L. Finnveden, Y. Jansson and T. Lindeberg, "Understanding when spatial transformer networks do not support invariance, and what to do about it," in ICPR2020 25th International Conference on Pattern Recognition, Milan, Italy, January 10-15, 2021, 2020.
F. Baldassarre et al., "Explanation-based Weakly-supervised Learning of Visual Relations with Graph Networks," in European Conference on Computer Vision, ECCV 2020, 2020.
H. Rezaei et al., "Facilitating the propagation of spiking activity in feedforward networks by including feedback," PloS Computational Biology, vol. 16, no. 8, 2020.
R. Hollandi et al., "nucleAIzer : A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer," Cell Systems, vol. 10, no. 5, pp. 453-458.e6, 2020.
A. Podobas, K. Sano and S. Matsuoka, "A Survey on Coarse-Grained Reconfigurable Architectures From a Performance Perspective," IEEE Access, vol. 8, pp. 146719-146743, 2020.
K. Dembrower et al., "Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload : a retrospective simulation study," Lancet Digital Health, vol. 2, no. 9, pp. E468-E474, 2020.
M. Karp et al., "Appendix to High-Performance Spectral Element Methods on Field-Programmable Gate Arrays," , 2020.
M. Lippi et al., "Latent Space Roadmap for Visual Action Planning of Deformable and Rigid Object Manipulation," in International Conference of Intelligent Robots and Systems 2020, 2020.
M. Mohagheghi Nejad, "Interaction of sensory and motor signals in the basal ganglia in health and disease," Doctoral thesis Stockholm : Kungliga Tekniska högskolan, TRITA-EECS-AVL, 2019:12, 2019.
C.-Y. Gao et al., "DCA for genome-wide epistasis analysis : the statistical genetics perspective," Physical Biology, vol. 16, no. 2, 2019.
O. Eriksson et al., "Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models," Bioinformatics, vol. 35, no. 2, pp. 284-292, 2019.
M. Wiesenberger et al., "Reproducibility, accuracy and performance of the FELTOR code and library on parallel computer architectures," Computer Physics Communications, vol. 238, pp. 145-156, 2019.
K. T. Blackwell et al., "Molecular mechanisms underlying striatal synaptic plasticity : relevance chronic alcohol consumption and seeking," European Journal of Neuroscience, vol. 49, no. 6, pp. 768-783, 2019.
G. H. Galal-Edeen et al., "HCI of Arabia : The challenges of HCI research in Egypt," interactions, vol. 26, no. 3, pp. 55-59, 2019.
L. Orellana et al., "Oncogenic mutations at the EGFR ectodomain structurally converge to remove a steric hindrance on a kinase-coupled cryptic epitope," Proceedings of the National Academy of Sciences of the United States of America, vol. 116, no. 20, pp. 10009-10018, 2019.
G. Hahn et al., "Portraits of communication in neuronal networks," Nature Reviews Neuroscience, vol. 20, no. 2, pp. 117-127, 2019.
S. Narasimhamurthy et al., "SAGE : Percipient Storage for Exascale Data Centric Computing," Parallel Computing, vol. 83, pp. 22-33, 2019.
G. Chen et al., "Multi-Cue Event Information Fusion for Pedestrian Detection With Neuromorphic Vision Sensors," Frontiers in Neurorobotics, vol. 13, 2019.
C. Simmendinger et al., "Interoperability strategies for GASPI and MPI in large-scale scientific applications," The international journal of high performance computing applications, vol. 33, no. 3, pp. 554-568, 2019.
F. Mirus et al., "Predicting vehicle behaviour using LSTMs and a vector power representation for spatial positions," in ESANN 2019 - Proceedings, 27th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 2019, pp. 113-118.