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Fekadu L. Bayisa
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Year
Large-scale modelling and forecasting of ambulance calls in northern Sweden using spatio-temporal log-Gaussian Cox processes
FL Bayisa, M Ådahl, P Rydén, O Cronie
Spatial Statistics 39, 100471, 2020
152020
Statistical learning in computed tomography image estimation
FL Bayisa, X Liu, A Garpebring, J Yu
Medical physics 45 (12), 5450-5460, 2018
122018
Adaptive algorithm for sparse signal recovery
FL Bayisa, Z Zhou, O Cronie, J Yu
Digital Signal Processing 87, 10-18, 2019
112019
Comparison of hidden Markov chain models and hidden Markov random field models in estimation of computed tomography images
K Kuljus, FL Bayisa, D Bolin, J Lember, J Yu
Communications in Statistics: Case Studies, Data Analysis and Applications 4 …, 2018
52018
Model-based Computed Tomography Image Estimation: Partitioning Approach
FL Bayisa, J Yu
arXiv preprint arXiv:1705.03799, 2017
42017
Regularised Semi-parametric Composite Likelihood Intensity Modelling of a Swedish Spatial Ambulance Call Point Pattern
FL Bayisa, M Ådahl, P Rydén, O Cronie
Journal of Agricultural, Biological and Environmental Statistics 28 (4), 664-683, 2023
12023
Spatial point process via regularisation modelling of ambulance call risk
FL Bayisa, M Ådahl, Patrik Rydén, O Cronie
https://arxiv.org/abs/2207.07814, 2022
2022
Model-based computed tomography image estimation: partitioning approach
FL Bayisa, J Yu
Journal of Applied Statistics 46 (14), 2627-2648, 2019
2019
Statistical methods in medical image estimation and sparse signal recovery
FL Bayisa
Umeå University, 2018
2018
Prediction of CT images from MR images with hidden Markov and random field models
F Bayisa, K Kuljus, A Johansson, D Bolin, J Yu
METMA VIII-8th International Workshop on Spatio-temporal Modelling, Valencia …, 2016
2016
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Articles 1–10