I hope that if I have time over the school year I can experiment with some of these items. If not, then I hope the project will be continued by somebody else.
Important and feasible
- Probabilistic output of SVMs
- Design a more reliable function, or maybe find another library for SVMs to do probabilistic output. The current implementation was rushed and is naive.
- Switch to one-against-one SVM and see if performance improves
- Graphical user interface and visual representation of results.
Important and exploratory
- Extending current system to original images with wings
- I did this very briefly and was able to achieve about 75% accuracy. This is just a rough estimate. There is a lot of room for creativity in solving this particular problem and I'll discuss a few ideas. The main idea is to do some sort of pre-processing or feature extraction to crop out the wasp body.
- Part-based detection by training on wasp bodies using SVMs
- Bilateral symmetry detection, centroids, other geometrical symmetry
- Identify wings and then segment out or ignore
- Any other ideas for "ignoring" the wings at feature extraction stage
- Finding optimal values for tuning parameters (almost all hard-coded numbers were chosen manually, and not automatically optimized).
I will edit this list as things come to mind.
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