Dec 21, 2022 · In this work, we propose and investigate a sandbox setup for rapid development and transparent evaluation of active learning in deep object detection.
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Abstract: Active learning as a paradigm in deep learning is especially important in applications involving intricate per- ception tasks such as object ...
In this work, we propose and investigate a sandbox setup for rapid development and transparent evaluation of active learning in deep object detection. Our ...
A sandbox setup for rapid development and transparent evaluation of active learning in deep object detection and allows for testing and evaluating data ...
This allows for testing and evaluating data acquisition and labeling strategies in under half a day and contributes to the transparency and development speed in ...
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. DOI: 10.5220/0012315400003660. Paper published under CC license (CC ...
This allows for testing and evaluating data acquisition and labeling strategies in under half a day and contributes to the transparency and development speed in ...
Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. T Riedlinger, M Schubert, K Kahl, H Gottschalk, M Rottmann. arXiv ...
Jul 11, 2024 · Towards Rapid Prototyping and Comparability in Active Learning for Deep Object Detection. VISIGRAPP (2): VISAPP 2024: 366-374. [c6]. view.