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Kim Bjerge
Kim Bjerge
Associate Professor, Aarhus University School of Engineering
Verified email at ase.au.dk
Title
Cited by
Cited by
Year
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
1872021
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
572021
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
442019
A living laboratory exploring mobile support for everyday life with diabetes.
AM Kanstrup, K Bjerge, JE Kristensen
Wireless personal communications 53 (3), 2010
412010
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
272021
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
192022
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
182017
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
122020
Guide for getting started with SystemC development
K Bjerge
Danish Technological Institute, 2007
112007
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
72021
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
62012
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
52021
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
42021
Towards a Methodology for Modelling and Validation of an Agricultural Vehicle’s Dynamics and Control
MP Christiansen, K Bjerge, G Edwards, PG Larsen
32012
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
22022
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
22022
Transitioning from Crescendo to INTO-CPS
K Lausdahl, K Bjerge, T Bokhove, F Groen, P Gorm
SCHOOL OF COMPUTING, 16, 2017
22017
3D impurity inspection of cylindrical transparent containers
M Kragh, K Bjerge, P Ahrendt
Measurement Science and Technology 28 (1), 017002, 2016
22016
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
12023
A generic and efficient convolutional neural network accelerator using HLS for a system on chip design
K Bjerge, J Schougaard, DE Larsen
arXiv, 2020
12020
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