Böttjer, T., Ørnskov Rønsch, G.
, Gonçalves Gomes, C. Â., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021).
Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.),
Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems: Proceedings of the Changeable, Agile, Reconfigurable and Virtual Production Conference and the World Mass Customization & Personalization Conference (pp. 431-439). Springer.
https://www.springerprofessional.de/en/data-driven-identification-of-remaining-useful-life-for-plastic-/19816878
Böttjer, T., Ørnskov Rønsch, G.
, Gomes, C., Ramanujan, D., Iosifidis, A. & Larsen, P. G. (2021).
Data-Driven Identification of Remaining Useful Life for Plastic Injection Moulds. In A.-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (Eds.),
Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems - Proceedings of the 8th Changeable, Agile, Reconfigurable and Virtual Production Conference CARV 2021 and 10th World Mass Customization and Personalization Conference MCPC 2021 (pp. 431-439). Springer.
https://doi.org/10.1007/978-3-030-90700-6_49
Böttjer, T., Tola, D., Kakavandi, F., Wewer, C. R., Ramanujan, D., Gomes, C., Larsen, P. G. & Iosifidis, A. (2023).
A review of unit level digital twin applications in the manufacturing industry.
CIRP Journal of Manufacturing Science and Technology,
45, 162-189.
https://doi.org/10.1016/j.cirpj.2023.06.011
Bording, T. S., Asif, M. R., Barfod, A. S., Larsen, J. J., Zhang, B., Grombacher, D. J., Christiansen, A. V., Engebretsen, K. W., Pedersen, J. B., Maurya, P. K. & Auken, E. (2021).
Machine learning based fast forward modelling of ground-based time-domain electromagnetic data.
Journal of Applied Geophysics,
187, Article 104290.
https://doi.org/10.1016/j.jappgeo.2021.104290
Böhnert, T.
, Rezaeiyan, Y., Claro, M. S., Benetti, L., Jenkins, A. S.
, Farkhani, H., Moradi, F. & Ferreira, R. (2023).
Weighted spin torque nano-oscillator system for neuromorphic computing.
Nature Communication Engineering,
2, Article 65.
https://doi.org/10.1038/s44172-023-00117-9
Bogomolov, S., Fitzgerald, J., Foldager, F. F., Gamble, C.
, Larsen, P. G., Pierce, K., Stankaitis, P. & Wooding, B. (2021).
Tuning Robotti: the Machine-assisted Exploration of Parameter Spaces in Multi-Models of a Cyber-Physical System. In J. Fitzgerald, T. Oda & H. D. Macedo (Eds.),
Proceedings of the 18th International Overture Workshop (pp. 50-65)
https://arxiv.org/pdf/2101.07261.pdf
Boersma, S., Bombois, X., Vanfretti, L.
, Peric, V., Gonzalez-Torres, J. C., Segur, R. & Benchaib, A. (2020).
Enhanced Power System Damping Estimation via Optimal Probing Signal Design. In
2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe Article 9215892 Institute of Electrical and Electronics Engineers Inc..
https://doi.org/10.23919/EPE20ECCEEurope43536.2020.9215892
Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N., Nørremark, M., Hameed, I. A. & Swain, K. C. (2011).
Robotic weed monitoring.
Acta Agriculturae Scandinavica, Section B - Soil & Plant Science,
61(3), 202-208.
https://doi.org/10.1080/09064711003796428
Bochtis, D. D., Sørensen, C. G., Fountas, S., Moysiadis, V. & Pardalos, P. M. (2022).
Preface.
Springer optimization and its applications,
184, v-xiii.
Bliddal, H.
, Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021).
Neural correlates of beat perception measured using ear-EEG: Bringing EEG music studies into the concert hall . Poster session presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.
Bjerge, K., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2022).
Accurate detection and identification of insects from camera trap images with deep learning. bioRxiv.
https://doi.org/10.1101/2022.10.25.513484
Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023).
Hierarchical Classification of Insects with Multitask Learning and Anomaly Detection. bioRxiv.
https://doi.org/10.1101/2023.06.29.546989
Bjerge, K., Alison, J., Dyrmann, M., Frigaard, C. E., Mann, H. M. R. & Høye, T. T. (2023).
Accurate detection and identification of insects from camera trap images with deep learning.
PLOS Sustainability and Transformation,
2(3).
https://doi.org/10.1371/journal.pstr.0000051
Bjerge, K., Geissmann, Q., Alison, J., Mann, H. M. R., Høye, T. T., Dyrmann, M. & Karstoft, H. (2023).
Hierarchical classification of insects with multitask learning and anomaly detection.
Ecological Informatics,
77, Article 102278.
https://doi.org/10.1016/j.ecoinf.2023.102278
Besson, M.
, Alison, J., Bjerge, K., Gorochowski, T. E.
, Høye, T. T., Jucker, T.
, Mann, H. M. R. & Clements, C. F. (2022).
Towards the fully automated monitoring of ecological communities.
Ecology Letters,
25(12), 2753-2775.
https://doi.org/10.1111/ele.14123
Berntsen, J., Rimestad, J., Lassen, J. T., Tran, D.
& Kragh, M. F. (2022).
Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences.
PLOS ONE,
17(2 ), Article e0262661.
https://doi.org/10.1371/journal.pone.0262661
Bennedsen, J., Edström, K., Guðjónsdóttir, M. S., Sæmundsdóttir, I., Kuptasthien, N., Roslöf, J. & Sripakagorn, A. (2021).
Editorial.
Proceedings of the International CDIO Conference, 1-2.