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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
Aerial Photography
Animals
Classifiers
Sensors
Smartphones
Physics & Astronomy
Aerial Photography

Publications

Recent
Spink, S. , Kamminga, J. W. , & Kamilaris, A. (2022). Improving the Annotation Efficiency for Animal Activity Recognition using Active Learning. In Measuring behavior 2022: 12th International Conference on Methods and Techniques in Behavioral Research, and 6th Seminar on Behavioral Methods (Vol. 2, pp. 51-58) https://doi.org/10.6084/m9.figshare.20066849
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

UT Research Information System

Google Scholar Link

Courses Academic Year  2022/2023

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.
 

Courses Academic Year  2021/2022

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