Christoph Kaeding
187e62a6f6
removed debug
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| activeLearning | %!s(int64=7) %!d(string=hai) anos | |
| evaluation | %!s(int64=8) %!d(string=hai) anos | |
| reweighting | %!s(int64=8) %!d(string=hai) anos | |
| .gitignore | %!s(int64=8) %!d(string=hai) anos | |
| COPYING | %!s(int64=8) %!d(string=hai) anos | |
| COPYING.LESSER | %!s(int64=8) %!d(string=hai) anos | |
| README.md | %!s(int64=8) %!d(string=hai) anos | |
| datasetAcquisition.py | %!s(int64=8) %!d(string=hai) anos | |
| example_setup.cfg | %!s(int64=8) %!d(string=hai) anos | |
| helperFunctions.py | %!s(int64=8) %!d(string=hai) anos | |
| methodSelection.py | %!s(int64=8) %!d(string=hai) anos |
README.md
Expected Model Output Change (EMOC)
Source code for methods described in the following papers:
Active learning and discovery of object categories in the presence of unnameable instances, C Käding, A Freytag, E Rodner, P Bodesheim, J Denzler, Computer Vision and Pattern Recognition (CVPR), 2015
Large-Scale Active Learning with Approximations of Expected Model Output Changes, C Käding, A Freytag, E Rodner, A Perino, J Denzler, German Conference on Pattern Recognition (GCPR), 2016
Watch, Ask, Learn, and Improve: A Lifelong Learning Cycle for Visual Recognition, C Käding, E Rodner, A Freytag, J Denzler, European Symposium on Artificial Neural Networks (ESANN), 2016
If you use parts of the code, please cite the corresponding papers.
Dependencies
- Python 2.7
- numpy
- scipy
- scikit-learn
Usage
- define setup (see example_setup.cfg)
- precompute setup (run evaluation/PrecomputeExperimentalSetup.py setup.cfg)
- start experiment (run evaluation/RunExperiment.py setup.cfg)
- see results (stored in results.mat)