Gislum, R., Thomsen, I. K., Hansen, E. M., Mortensen, A. K., Larsen, R. & Olesen, J. E., (2021).
Analyser i pilotprojekt om biomasse på baggrund af data fra forsøgsår 2020, Nr. 2021-0206943, 18 s., maj 05, 2021. Rådgivningsnotat fra DCA – National Center for Fødevarer og Jordbrug
Somerville, G. J., Mathiassen, S. K., Melander, B., Bøjer, O. M.
& Nyholm Jørgensen, R. (2021).
Analysing the number of images needed to create robust variable spray maps.
Precision Agriculture,
22(5), 1377-1396.
https://doi.org/10.1007/s11119-021-09800-3
Bjerge, K., Nielsen, J. B., Sepstrup, M. V., Helsing-Nielsen, F.
& Høye, T. T. (2021).
An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning.
Sensors (Switzerland),
21(2), Artikel 343.
https://doi.org/10.3390/s21020343
Ahmadi, H.
, Rafiei Foroushani, M., Afshari-Igder, M.
, Gheisarnejad Chirani, M. & Khooban, M. H. (2021).
An Energy Efficient Solution for Fuel Cell Heat Recovery in Zero-Emission Ferry Boats: Deep Deterministic Policy Gradient.
I E E E Transactions on Vehicular Technology,
70(8), 7571-7581. Artikel 9477203.
https://doi.org/10.1109/TVT.2021.3094899.
Larsen, J. J., Griffiths, M., Vang, M., Liu, L. & Grombacher, D. (2021).
Apsu - A compact surface NMR instrument for groundwater investigations.
SEG Technical Program Expanded Abstracts,
2021-September, 3135-3139.
https://doi.org/10.1190/segam2021-3582046.1
Tan, S., Mortensen, A. K., Ma, X.
, Boelt, B. & Gislum, R. (2021).
Assessment of grass lodging using texture and canopy height distribution features derived from UAV visual-band images.
Agricultural and Forest Meteorology,
308-309, Artikel 108541.
https://doi.org/10.1016/j.agrformet.2021.108541
Kass, M. A., Auken, E., Larsen, J. J. & Christiansen, A. V. (2021).
A towed magnetic gradiometer array for rapid, detailed imaging of utility, geological, and archaeological targets.
Geoscientific Instrumentation, Methods and Data Systems,
10(2), 313-323.
https://doi.org/10.5194/gi-10-313-2021
Nguyen, A. Q., Nguyen, H. T., Tran, V. C.
, Pham, H. X. & Pestana, J. (2021).
A Visual Real-time Fire Detection using Single Shot MultiBox Detector for UAV-based Fire Surveillance. I S. Bahk, P. Tran-Gia, J. Van der Spiegel & N. X. Quynh (red.),
2020 IEEE Eighth International Conference on Communications and Electronics (ICCE) (s. 338-343). IEEE.
https://doi.org/10.1109/ICCE48956.2021.9352080
Dyrmann, M., Mortensen, A. K., Linneberg, L.
, Høye, T. T. & Bjerge, K. (2021).
Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning.
Sensors (Switzerland),
21(18), Artikel 6126.
https://doi.org/10.3390/s21186126
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. I A-L. Andersen, R. Andersen, T. D. Brunoe, M. Stoettrup Schioenning Larsen, K. Nielsen, A. Napoleone & S. Kjeldgaard (red.),
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 (s. 431-439). Springer.
https://doi.org/10.1007/978-3-030-90700-6_49
Høye, T. T., Ärje, J., Bjerge, K., Hansen, O. L. P., Iosifidis, A., Leese, F.
, Mann, H. M. R., Meissner, K.
, Melvad, C. & Raitoharju, J. (2021).
Deep learning and computer vision will transform entomology.
Proceedings of the National Academy of Sciences,
118(2), Artikel e2002545117.
https://doi.org/10.1073/pnas.2002545117
Cao, G.
, Iosifidis, A., Gabbouj, M., Raghavan, V. & Gottumukkala, R. (2021).
Deep Multi-view Learning to Rank.
IEEE Transactions on Knowledge and Data Engineering,
33(4), 1426-1438. Artikel 8845659.
https://doi.org/10.1109/TKDE.2019.2942590
Chen, Q., Lang, X., Lu, S.
, Rehman, N. U., Xie, L. & Su, H. (2021).
Detection and root cause analysis of multiple plant-wide oscillations using multivariate nonlinear chirp mode decomposition and multivariate Granger causality.
Computers and Chemical Engineering,
147, Artikel 107231.
https://doi.org/10.1016/j.compchemeng.2021.107231
Asif, M. R., Bording, T. S., Barfod, A. S., Grombacher, D. J., Maurya, P. K., Christiansen, A. V., Auken, E. & Larsen, J. J. (2021).
Effect of Data Pre-Processing on the Performance of Neural Networks for 1-D Transient Electromagnetic Forward Modeling.
IEEE Access,
9, 34635-34646.
https://doi.org/10.1109/ACCESS.2021.3061761
Kiranyaz, S., Malik, J., Abdallah, H. B., Ince, T.
, Iosifidis, A. & Gabbouj, M. (2021).
Exploiting heterogeneity in operational neural networks by synaptic plasticity.
Neural Computing and Applications,
33(13), 7997-8015.
https://doi.org/10.1007/s00521-020-05543-w
Passalis, N., Kanniainen, J., Gabbouj, M.
, Iosifidis, A. & Tefas, A. (2021).
Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization.
Journal of Signal Processing Systems,
93(10), 1235-1251.
https://doi.org/10.1007/s11265-020-01624-0
Pham, X. H., Bozcan, I., Sarabakha, A., Haddadin, S.
& Kayacan, E. (2021).
GateNet: An Efficient Deep Neural Network Architecture for Gate Perception Using Fish-Eye Camera in Autonomous Drone Racing. Afhandling præsenteret på 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems, Prag, Tjekkiet.
https://sarabakha.info/files/papers/conference/IROS_2021.pdf
Gautam, C., Tiwari, A., Mishra, P. K., Suresh, S.
, Iosifidis, A. & Tanveer, M. (2021).
Graph-Embedded Multi-Layer Kernel Ridge Regression for One-Class Classification.
Cognitive Computation,
13(2), 552-569.
https://doi.org/10.1007/s12559-020-09804-7
Laakom, F., Raitoharju, J., Nikkanen, J.
, Iosifidis, A. & Gabbouj, M. (2021).
INTEL-TAU: A Color Constancy Dataset.
IEEE Access,
9, 39560-39567. Artikel 9371681.
https://doi.org/10.1109/ACCESS.2021.3064382
Feng, H., Gomes, C., Thule, C., Lausdahl, K., Iosifidis, A. & Larsen, P. G. (2021).
Introduction to Digital Twin Engineering. I C. R. Martin, M. J. Blas & A. I. Psijas (red.),
2021 Annual Modeling and Simulation Conference (ANNSIM) (s. 1-12). IEEE.
https://doi.org/10.23919/ANNSIM52504.2021.9552135
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, Artikel 104290.
https://doi.org/10.1016/j.jappgeo.2021.104290
Bajovic, D.
, Bakhtiarnia, A., Bravos, G., Brutti, A., Burkhardt, F., Cauchi, D., Chazapis, A., Cianco, C., Dall'Asen, N., Delic, V., Dimou, C., Djokic, D., Escobar-Molero, A.
, Esterle, L., Eyben, F., Farella, E., Festi, T., Geromitsos, A., Giakoumakis, G. ... Zammit, J. (2021).
MARVEL: Multimodal Extreme Scale Data Analytics for Smart Cities Environments. I
2021 International Balkan Conference on Communications and Networking, BalkanCom 2021 (s. 143-147). IEEE.
https://doi.org/10.1109/BalkanCom53780.2021.9593258
Tran, D. T., Yamac, M., Degerli, A., Gabbouj, M.
& Iosifidis, A. (2021).
Multilinear compressive learning.
IEEE Transactions on Neural Networks and Learning Systems,
32(4), 1512-1524. Artikel 9070152.
https://doi.org/10.1109/TNNLS.2020.2984831