minor

.gitignore

@@ -1 +1,3 @@
-*.pyc
+*.pyc
+*.bak
+*.swp

README.md

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 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
+- 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
+- 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
+- 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.

README.md.bak

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-## Expected Model Output Change (EMOC)
-
-Source code for methods descibed 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
-
-1. define setup (see example_setup.cfg)
-2. precompute setup (run evaluation/PrecomputeExperimentalSetup.py setup.cfg)
-3. start experiment (run evaluation/RunExperiment.py setup.cfg)
-4. see results (stored in results.mat)