(48) X-ray microtomography and linear discriminant analysis enable extraction of embolism-related acoustic emissionsN.J.F. De Baerdemaker, M. Stock, J. Van Den Bulcke, B. De Baets, L. Van Hoorebeke and K. Steppe(2019) PLANT METHODS. 15, 153. |
(47) Randomized lasso links microbial taxa with aquatic functional groups inferred from flow cytometryP. Rubbens, M. Schmidt, R. Props, B. Biddanda, N. Boon, W. Waegeman and V. Denef(2019) MSYSTEMS. 4, 00093-19. |
(46) Guiding mineralization co-culture discovery using Bayesian optimizationA.J. Daly, M. Stock, J.M. Baetens and B. De Baets(2019) ENVIRONMENTAL SCIENCE AND TECHNOLOGY. 53, 14459-14469. |
(45) A statistical approach to the identification of Diploid Cellular Automata based on incomplete observationsW. Bolt, A. Bolt, B. Wolnik, J.M. Baetens and B. De Baets(2019) BIOSYSTEMS. 186, 103976. |
(44) A protocol for automated timber species identification using metabolome profilingV. Deklerck, T. Mortier, N. Goeders, R.B. Cody, W. Waegeman, E. Espinoza, J. Van Acker, J. Van den Bulcke and H. Beeckman(2019) WOOD SCIENCE AND TECHNOLOGY. 53, 953-965. |
(43) A hospital wide predictive model for unplanned readmission using hierarchical ICD dataM. Deschepper, K. Eeckloo, D. Vogelaers and W. Waegeman(2019) COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 173, 177-183. |
(42) Lattice-based versus lattice-free individual-based models: impact on coexistence in competitive communitiesA.J. Daly, W. Quaghebeur, T.M.A. Depraetere, J.M. Baetens and B. De Baets(2019) NATURAL COMPUTING. 18, 855-864. |
(41) Contour detection based on anisotropic edge strength and hierarchical superpixel contrastG. Wang and B. De Baets(2019) SIGNAL, IMAGE AND VIDEO PROCESSING. 13, 1657-1665. |
(40) Possibilistic compositions and state functions: application to the order promising process for perishablesH. Grillo, M.M.E. Alemany, A. Ortiz and B. De Baets(2019) INTERNAT. JOURNAL OF PRODUCTION RESEARCH. 57, 7006-7031. |
(39) EcologicalNetworks.jl: analysing ecological networks of species interactionsT. Poisot, Z. Bélisle, L. Hoebeke, M. Stock and P. Szefer(2019) ECOGRAPHY. 42, 1850-1861. |
(38) The sample monomode and an associated test for discrete monomodalityR. Pérez-Fernández and B. De Baets(2019) COMMUNICATIONS IN STATISTICS: THEORY AND METHODS. 48, 5419-5426. |
(37) Kernel-based distance metric learning for supervised k-means clusteringB. Nguyen and B. De Baets(2019) IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS. 30, 3084-3095. |
(36) Multiscale edge detection using first-order derivative of anisotropic Gaussian kernelsG. Wang, C. Lopez-Molina and B. De Baets(2019) JOURNAL OF MATHEMATICAL IMAGING AND VISION. 61, 1096-1111. |
(35) Real-time prediction of influenza outbreaks in BelgiumG.H.B. Miranda, J.M. Baetens, N. Bossuyt, O.M. Bruno and B. De Baets(2019) EPIDEMICS. 28, 100341. |
(34) Analysis of spatio-temporal fungal growth dynamics under different environmental conditionsL. De Ligne, G. Vidal-Diez de Ulzurrun, J.M. Baetens, J. Van Den Bulcke, J. Van Acker and B. De Baets(2019) IMA FUNGUS. 10, 7. |
(33) All binary number-conserving cellular automata based on adjacent cells are intrinsically one-dimensionalB. Wolnik and B. De Baets(2019) PHYSICAL REVIEW E. 100, 022126. |
(32) The impact of hurricanes on biogeochemical indicators of the Exclusive Economic Zone of CubaD. Avila-Alonso, J.M. Baetens, R. Cardenas and B. De Baets(2019) REMOTE SENSING OF ENVIRONMENT. 233, 111339. |
(31) On the compatibility of a ternary relation with a binary fuzzy relationO. Barkat, L. Zedam and B. De Baets(2019) INTERNAT. J. UNCERTAINTY, FUZZINESS AND KNOWLEDGE-BASED SYSTEMS. 27, 595-612. |
(30) Learning single-cell distances from cytometry dataB. Nguyen, P. Rubbens, F.-M. Kerckhof, N. Boon, B. De Baets and W. Waegeman(2019) CYTOMETRY PART A. 95, 782-791. |
(29) A two-layer representation of four-state reversible number-conserving 2D cellular automataA. Dzedzej, B. Wolnik, M. Dziemiańczuk, A. Nenca, J.M. Baetens and B. De Baets(2019) JOURNAL OF STATISTICAL MECHANICS: THEORY AND EXPERIMENT. 2019, 073202. |
(28) On the role of monometrics in penalty-based data aggregationR. Pérez-Fernández and B. De Baets(2019) IEEE TRANSACTIONS ON FUZZY SYSTEMS. 27, 1456-1468. |
(27) Cyt-Geist: Current and Future Challenges in Cytometry: Reports of the CYTO 2018 Conference WorkshopsK. Czechowska, J. Lannigan, L. Wang, J. Arcidiacono, T.M. Ashhurst, R.M. Barnard, S. Bauer, C. Bispo, D.L. Bonilla, R.R. Brinkman, M. Cabanski, H. Chang, L. Chakrabarti, G. Chojnowski, B. Cotleur, H. Degheidy, G.V. Dela Cruz, S. Eck, J. Elliott, R. Errington, A. Filby, D. Gagnon, R. Gardner, C. Green, M. Gregory, C.J. Groves, C. Hall, F. Hammes, M. Hedrick, R. Hoffman, J. Icha, J. Ivaska, D.C. Jenner, D. Jones, F-M. Kerckhof, C. Kukat, D. Lanham, S. Leavesley, M. Lee, S. Lin-Gibson, V. Litwin, Y. Liu, J. Molloy, J.S. Moore, S. Müller, J. Nedbal, R. Niesner, N. Nitta, B. Ohlsson-Wilhelm, N.E. Paul, S. Perfetto, Z. Portat, R. Props, S. Radtke, R. Rayanki, A. Rieger, S. Rogers, P. Rubbens, R. Salomon, M. Schiemann, J. Sharpe, S.U. Sonder, J.J. Stewart, Y. Sun, H. Ulrich, G. Van Isterdael, A. Vitaliti, C. van Vreden, M. Weber, J. Zimmermann, G. Vacca, P. Wallace and A. Tárnok(2019) CYTOMETRY PART A. 95, 598-644. |
(26) Spoilage evaluation of raw Atlantic salmon (Salmo salar) stored under modified atmospheres by multivariate statistics and augmented ordinal regressionL. Kuuliala, M. Sader, A. Solimeo, R. Pérez-Fernández, M. Vanderroost, B. De Baets, B. De Meulenaer, P. Ragaert and F. Devlieghere(2019) INTERNAT. J. OF FOOD MICROBIOLOGY. 303, 46-57. |
(25) A taxonomy of monotonicity properties for the aggregation of multidimensional dataR. Pérez-Fernández, B. De Baets and M. Gagolewski(2019) INFORMATION FUSION. 52, 322-334. |
(24) Topologies induced by the representation of a betweenness relation as a family of order relationsH. Zhang, R. Pérez-Fernández and B. De Baets(2019) TOPOLOGY AND ITS APPLICATIONS. 258, 100-114. |
(23) An ontology to standardize nutritional epidemiologic research output: from paper-based standards to linked contentC. Yang, H. Ambayo, B. De Baets, P. Kolsteren, N. Thanintorn, D. Hawwash, J. Bouwman, A. Bronselaer, F. Pattyn and C. Lachat(2019) NUTRIENTS. 11, 1300. |
(22) Cutting levels of the winning probability relation of random variables pairwisely coupled by a same Frank copulaB. De Baets and H. De Meyer(2019) INTERNAT. J. APPROXIMATE REASONING. 112, 22-36. |
(21) Coculturing bacteria leads to reduced phenotypic heterogeneitiesJ. Heyse, B. Buysschaert, R. Props, P. Rubbens, A. Skirtach, W. Waegeman and N. Boon(2019) APPLIED AND ENVIRONMENTAL MICROBIOLOGY. 85, e02814-18. |
(20) DeepRibo: a neural network for the precise gene annotation of prokaryotes by combining ribosome profiling signal and binding site patternsJ. Clauwaert, G. Menschaert and W. Waegeman(2019) NUCLEIC ACIDS RESEARCH. 47, e36. |
(19) A validated expert-based habitat suitability assessment for Eagle Owls in Limburg, the NetherlandsS. Van Nieuland, J.M. Baetens, S. Vriens, R. Janssen and B. De Baets(2019) EUROPEAN JOURNAL OF WILDLIFE RESEARCH. 65, 48. |
(18) Two-dimensional affine continuous cellular automata solving the relaxed density classification problemM. Dembowski, B. Wolnik, W. Bolt, J.M. Baetens and B. De Baets(2019) JOURNAL OF CELLULAR AUTOMATA. 14, 191-212. |
(17) Inter- and intrafield distribution of cereal leaf beetle species (Coleoptera: Chrysomelidae) in Belgian winter wheatE. Van de Vijver, S. Landschoot, M. Van Roie, F. Temmerman, J. Dillen, K. De Ceuleners, G. Smagghe, B. De Baets and G. Haesaert(2019) ENVIRONMENTAL ENTOMOLOGY. 48, 276-283. |
(16) The acclamation consensus state and an associated ranking ruleR. Pérez-Fernández and B. De Baets(2019) INTERNAT. J. OF INTELLIGENT SYSTEMS. 34, 1223-1247. |
(15) Assessing the potential of the Qualitative Trajectory Calculus to detect gait pathologies: A case study of children with developmental coordination disorderJ. Beernaerts, R. Derie, B. Nguyen, P. Vansteenkiste, B. De Baets, F.J.A. Deconinck, M. Lenoir, D. De Clercq and N. Van de Weghe(2019) COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING. 22, 64-70. |
(14) Predicting children’s food choice using check-all-that-apply questionsJ. Verwaeren, X. Gellynck, S. Lagast and J. Schouteten(2019) JOURNAL OF SENSORY STUDIES. 34, e12471. |
(13) Multi-target prediction: a unifying view on problems and methodsW. Waegeman, K. Dembczyński and E. Hüllermeier(2019) DATA MINING AND KNOWLEDGE DISCOVERY. 33, 293-324. |
(12) Noise-robust line detection using normalized and adaptive second-order anisotropic Gaussian kernelsG. Wang, C. Lopez-Molina, G. Vidal-Diez De Ulzurrun and B. De Baets(2019) SIGNAL PROCESSING. 160, 252-262. |
(11) Multivariate winning probabilitiesI. Montes, S. Montes and B. De Baets(2019) FUZZY SETS AND SYSTEMS. 362, 129-143. |
(10) Left- and right-compatibility of order relations and fuzzy tolerance relationsL. Zedam, H. Bouremel and B. De Baets(2019) FUZZY SETS AND SYSTEMS. 360, 65-81. |
(9) Comparing a standardized to a product-specific emoji list for evaluating food products by childrenJ. Schouteten, J. Verwaeren, X. Gellynck and V.L. Almli(2019) FOOD QUALITY AND PREFERENCE. 72, 86–97. |
(8) Integrating expert and novice evaluations for augmenting ordinal regression modelsM. Sader, J. Verwaeren, R. Pérez-Fernández and B. De Baets(2019) INFORMATION FUSION. 51, 1-9. |
(7) Rift Valley fever: an open-source transmission dynamics simulation modelR. Sumaye, F. Jansen, D. Berkvens, B. De Baets, E. Geubels, E. Thiry and M. Krit(2019) PLOS ONE. 14, e0209929. |
(6) The superdominance relation, the positional winner, and more missing links between Borda and CondorcetR. Pérez-Fernández and B. De Baets(2019) JOURNAL OF THEORETICAL POLITICS. 31, 46-65. |
(5) On the degree of asymmetry of a quasi-copula with respect to a curveB. De Baets, H. De Meyer and T. Jwaid(2019) FUZZY SETS AND SYSTEMS. 354, 84-103. |
(4) On the lattice structure of the set of supermodular quasi-copulasJ.J. Arias García and B. De Baets(2019) FUZZY SETS AND SYSTEMS. 354, 74-83. |
(3) Kernel distance metric learning using pairwise constraints for person re-identificationB. Nguyen and B. De Baets(2019) IEEE TRANSACTIONS ON IMAGE PROCESSING. 28, 589-600. |
(2) An efficient method for clustered multi-metric learningB. Nguyen, F. Ferri, C. Morell and B. De Baets(2019) INFORMATION SCIENCES. 471, 149-163. |
(1) A method based on the Levenshtein distance metric for the comparison of multiple movement patterns described by matrix sequences of different lengthJ. Beernaerts, E. Debever, M. Lenoir, B. De Baets and N. Van de Weghe(2019) EXPERT SYSTEMS WITH APPLICATIONS. 115, 373-385. |