Kim Bjerge
Kim Bjerge
Associate Professor, Aarhus University School of Engineering
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Cited by
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Deep learning and computer vision will transform entomology
TT Hye, J rje, K Bjerge, OLP Hansen, A Iosifidis, F Leese, HMR Mann, ...
Proceedings of the National Academy of Sciences 118 (2), e2002545117, 2021
Towards the fully automated monitoring of ecological communities
M Besson, J Alison, K Bjerge, TE Gorochowski, TT Hye, T Jucker, ...
Ecology Letters 25 (12), 2753-2775, 2022
An automated light trap to monitor moths (Lepidoptera) using computer vision-based tracking and deep learning
K Bjerge, JB Nielsen, MV Sepstrup, F Helsing-Nielsen, TT Hye
Sensors 21 (2), 343, 2021
Real-time insect tracking and monitoring with computer vision and deep learning
K Bjerge, HMR Mann, TT Hye
Remote Sensing in Ecology and Conservation, 2021
A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony
K Bjerge, CE Frigaard, PH Mikkelsen, TH Nielsen, M Misbih, P Kryger
Computers and Electronics in Agriculture 164, 104898, 2019
A living laboratory exploring mobile support for everyday life with diabetes
AM Kanstrup, K Bjerge, JE Kristensen
Wireless personal communications 53, 395-408, 2010
Accurate detection and identification of insects from camera trap images with deep learning
K Bjerge, J Alison, M Dyrmann, CE Frigaard, HMR Mann, TT Hye
PLOS Sustainability and Transformation 2 (3), e0000051, 2023
Enhancing non-technical skills by a multidisciplinary engineering summer school
PG Larsen, EL Kristiansen, J Bennedsen, K Bjerge
European Journal of Engineering Education 42 (6), 1076-1096, 2017
A light trap and computer vision system to detect and classify live moths (Lepidoptera) using tracking and deep learning
K Bjerge, JB Nielsen, M Videbk Sepstrup, F Helsing-Nielsen, TT Hye
bioRxiv, 2020.03. 18.996447, 2020
A scalable and efficient convolutional neural network accelerator using HLS for a system-on-chip design
K Bjerge, JH Schougaard, DE Larsen
Microprocessors and microsystems 87, 104363, 2021
Guide for getting started with SystemC development
K Bjerge
Danish Technological Institute, 2007
Accurate image-based identification of macroinvertebrate specimens using deep learning—How much training data is needed?
TT Hye, M Dyrmann, C Kjr, J Nielsen, M Bruus, CL Mielec, ...
PeerJ 10, e13837, 2022
Camera assisted roadside monitoring for invasive alien plant species using deep learning
M Dyrmann, AK Mortensen, L Linneberg, TT Hye, K Bjerge
Sensors 21 (18), 6126, 2021
Vibration signatures in ball bearings as a function of lubricant viscosity ratio κ, under alternating lubrication conditions
MO Jakobsen, ES Herskind, K Bjerge, P Ahrendt, CF Pedersen, ...
Tribology International 156, 106840, 2021
Hierarchical classification of insects with multitask learning and anomaly detection
K Bjerge, Q Geissmann, J Alison, HMR Mann, TT Hye, M Dyrmann, ...
Ecological Informatics 77, 102278, 2023
Supporting the Partitioning process in Hardware/Software Co-design with VDM-RT
JAE Isasa, PG Larsen, K Bjerge
Nico Plat, Claus Ballegaard Nielsen and Steve Riddle (Eds.), 5, 2012
Object Detection of Small Insects in Time-Lapse Camera Recordings
K Bjerge, CE Frigaard, H Karstoft
Sensors 23 (16), 7242, 2023
Computer vision and deep learning in insects for food and feed production: A review
S Nawoya, F Ssemakula, R Akol, Q Geissmann, H Karstoft, K Bjerge, ...
Computers and Electronics in Agriculture 216, 108503, 2024
A mobile observatory powered by sun and wind for near real time measurements of atmospheric, glacial, terrestrial, limnic and coastal oceanic conditions in remote off-grid areas
S Rysgaard, K Bjerge, W Boone, E Frandsen, M Graversen, TT Hye, ...
HardwareX 12, e00331, 2022
Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects
DB Roy, J Alison, TA August, M Blisle, K Bjerge, JJ Bowden, MJ Bunsen, ...
Philosophical Transactions of the Royal Society B 379 (1904), 20230108, 2024
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