Online handwritten gesture recognition based on Takagi-Sugeno fuzzy models
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we present a new method for incremental online handwritten gesture recognition based on fuzzy rules. This approach allows starting from a scratch with no previously learned classes and adding new ones lifelong. Unlike methods based on evolving mountain clustering, our approach suits incremental concept better. We introduce a new method for evolving clustering and usage of incremental density measurement for determining the membership function which significantly improves the results. Density measurement as membership function allows using only few parameters instead of the costly covariance matrices and does not require any estimating by averaging and thus preventing from information lost. We also introduce a new set of features based on a shape of gestures. Combination of these new system characteristics thus lowers memory and computational requirements while significantly increasing recognition rate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it