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dr. J.W. Kamminga (Jacob)

Researcher

About Me

Jacob Kamminga completed his Ph.D. in animal activity recognition at the University of Twente in 2020. He used machine learning models as activity classifiers to recognize various activities of animals using motion data on resource-constrained devices (edge-AI). Currently, he is studying active learning and human-in-the-loop AI training. Furthermore, he is interested in unsupervised representation learning to exploit unlabeled data. Other areas of his expertise are data acquisition, processing, and annotation. 

Since 2021 Jacob has been the digital species identification team leader within the ARISE biodiversity project. The digital species identification team builds services that support developing and deploying AI algorithms that detect and identify species from various digital media such as sound, images, and radar.

Expertise

Engineering & Materials Science
Accelerometers
Acoustic Waves
Acoustics
Animals
Classifiers
Feature Extraction
Sensors
Smartphones

Publications

Recent
Kamminga, J. W. , Meratnia, N. , & Havinga, P. J. M. (2019). Dataset: Horse Movement Data and Analysis of its Potential for Activity Recognition. 22-25. Paper presented at 2nd Workshop on Data Acquisition To Analysis, DATA 2019, New York, New York, United States. https://doi.org/10.1145/3359427.3361908
Kamminga, J. W., Jones, M., Seppi, K. , Meratnia, N. , & Havinga, P. J. M. (2019). Synchronization between Sensors and Cameras in Movement Data Labeling Frameworks. In DATA'19: Proceedings of the 2nd Workshop on Data Acquisition To Analysis (pp. 37-39) https://doi.org/10.1145/3359427.3361920
Le, D. V. , Kamminga, J. , Scholten, H. , & Havinga, P. J. M. (2018). A Framework to Measure Reliance of Acoustic Latency on Smartphone Status. In 2018 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom Workshops 2018 (pp. 348-354). [8480354] IEEE. https://doi.org/10.1109/PERCOMW.2018.8480354
Kamminga, J. W., Bisby, H. C. , Le, D. V. , Meratnia, N. , & Havinga, P. J. M. (2017). Generic online animal activity recognition on collar tags. In UbiComp'17: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers (pp. 597-606). ACM Press. https://doi.org/10.1145/3123024.3124407

UT Research Information System

Google Scholar Link

Courses Academic Year  2021/2022

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.
 

Contact Details

Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

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University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11)
Hallenweg 19
7522NH  Enschede
The Netherlands

Navigate to location

Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling
P.O. Box 217
7500 AE Enschede
The Netherlands