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Kim Bjerge

Aarhus University

Denmark

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Research Interests

Zoology

40%

Entomology

60%

Computer Vision

50%

Insect

50%

Deep Learning

20%

Swarm Intelligence

20%

Gpu Computing

10%

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Articles16

Prediction of black soldier fly larval sex and morphological traits using computer vision and deep learning

Article Link

Year:

2025

Towards edge processing of images from insect camera traps

Article Link

Year:

2025

ScannerVision: Scanner-based image acquisition of medically important arthropods for the development of computer vision and deep learning models

Article Link

Year:

2025

Computer vision and deep learning in insects for food and feed production: A review

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Year:

2024

Towards a standardized framework for AI-assisted, image-based monitoring of nocturnal insects

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Year:

2024

A deep learning pipeline for time-lapse camera monitoring of insects and their floral environments

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Year:

2024

Hierarchical classification of insects with multitask learning and anomaly detection

Article Link

Year:

2023

Accurate detection and identification of insects from camera trap images with deep learning

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Year:

2023

Object Detection of Small Insects in Time-Lapse Camera Recordings

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Year:

2023

Towards the fully automated monitoring of ecological communities

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Year:

2022

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

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Year:

2022

Accurate image-based identification of macroinvertebrate specimens using deep learning — How much training data is needed?

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Year:

2022

Real‐time insect tracking and monitoring with computer vision and deep learning

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Year:

2022

A scalable and efficient convolutional neural network accelerator using HLS for a system-on-chip design

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Year:

2021

Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning

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Year:

2021

Vibration signatures in ball bearings as a function of lubricant viscosity ratio κ, under alternating lubrication conditions

Article Link

Year:

2021

Collaborators19

Maxim Larrivée

Head of section

Insectarium de Montréal

CANADA

Toke T. Hoye

Professor

Aarhus University

DENMARK

Christopher Clements

University of Bristol

UNITED KINGDOM

Claus Melvad

Aarhus University

DENMARK

Christian Fischer Pedersen

Associate Professor

Aarhus University

DENMARK

Quentin Geissmann

Aarhus University

DENMARK

Grum Gebreyesus Teklewold

Aarhus University

DENMARK

Henrik Karstoft

Aarhus University

DENMARK

Jeffrey Kerby

Aarhus University

DENMARK

Lise Lotte Sørensen

Aarhus University

DENMARK

Mikhail Mastepanov

Aarhus University

DENMARK

Mads Dyrmann

Aarhus University

DENMARK

Tenna Riis

Aarhus University

DENMARK

Torben R. Christensen

Aarhus University

DENMARK

Anders Krogh Mortensen

Aarhus University

DENMARK

Marianne Bruus

Aarhus University

DENMARK

Jamie Alison

Aarhus University

DENMARK

Marc Mazerolle

Professor

Laval University

CANADA

Tommaso Jucker

University of Bristol

UNITED KINGDOM

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