A Living Laboratory Exploring Mobile Support for Everyday Life with Diabetes. - Anne Marie Kanstrup; Kim Bjerge; Jens Enevold Kristensen (Wirel. Pers. Commun., 2010)

A computer vision system to monitor the infestation level of Varroa destructor in a honeybee colony. - Kim Bjerge; Carsten Eie Frigaard; Peter Høgh Mikkelsen; Thomas Holm Nielsen; Michael Misbih; Per Kryger (Comput. Electron. Agric., 2019)

A system on programmable chip design of a digitizer with improved trapezoidal filter validation. - Kim Bjerge; Hans O. U. Fynbo; Jacob G. Johansen (Microprocess. Microsystems, 2019)

A generic and efficient convolutional neural network accelerator using HLS for a system on chip design. - Kim Bjerge; Jonathan Schougaard; Daniel Ejnar Larsen (CoRR, 2020)

An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning. - Kim Bjerge; Jakob Bonde Nielsen; Martin Videbæk Sepstrup; Flemming Helsing-Nielsen; Toke Thomas Høye (Sensors, 2021)

Camera Assisted Roadside Monitoring for Invasive Alien Plant Species Using Deep Learning. - Mads Dyrmann; Anders Krogh Mortensen; Lars Linneberg; Toke Thomas Høye; Kim Bjerge (Sensors, 2021)

A scalable and efficient convolutional neural network accelerator using HLS for a system-on-chip design. - Kim Bjerge; Jonathan Schougaard; Daniel Ejnar Larsen (Microprocess. Microsystems, 2021)

Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. - Kim Bjerge; Carsten Eie Frigaard; Henrik Karstoft (CoRR, 2022)

Object Detection of Small Insects in Time-Lapse Camera Recordings. - Kim Bjerge; Carsten Eie Frigaard; Henrik Karstoft (Sensors, 2023)

Hierarchical classification of insects with multitask learning and anomaly detection. - Kim Bjerge; Quentin Geissmann; Jamie Alison; Hjalte M. R. Mann; Toke Thomas Høye; Mads Dyrmann; Henrik Karstoft (Ecol. Informatics, 2023)

Few-Shot Learning with Novelty Detection. - Kim Bjerge; Paul Bodesheim; Henrik Karstoft (DeLTA (1), 2024)

Insect Identification in the Wild: The AMI Dataset. - Aditya Jain; Fagner Cunha; Michael James Bunsen; Juan Sebastián Cañas; Léonard Pasi; Nathan Pinoy; Flemming Helsing; JoAnne Russo; Marc Botham; Michael Sabourin; Jonathan Fréchette; Alexandre Anctil; et al. (ECCV (37), 2024)

A deep learning pipeline for time-lapse camera monitoring of insects and their floral environments. - Kim Bjerge; Henrik Karstoft; Hjalte M. R. Mann; Toke Thomas Høye (Ecol. Informatics, 2024)

Computer vision and deep learning in insects for food and feed production: A review. - Sarah Nawoya; Frank Ssemakula; Roseline Akol; Quentin Geissmann; Henrik Karstoft; Kim Bjerge; Cosmas Mwikirize; Andrew Katumba; Grum Gebreyesus (Comput. Electron. Agric., 2024)

Deep Image Clustering with Model-Agnostic Meta-Learning. - Kim Bjerge; Paul Bodesheim; Henrik Karstoft (VISIGRAPP (2): VISAPP, 2025)