FES: A System for Combining Face, Ear and Signature Biometrics Using Rank Level Fusion
Why this work is in the frame
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Bibliographic record
Abstract
Performance rate of unimodal biometric system is often reduced due to physiological defects, user mode and the environment. Multibiometric systems seek to alleviate some of these drawbacks by providing multiple evidences of the same identity. In this paper, we develop a multimodal biometric system, FES, based on principal component analysis (PCA) and Fisher's linear discriminant (FLD) methods that will use face, ear and signature for identity identification and rank level fusion for consolidate the results obtained from these monomodal matchers. The ranks of individual matchers are combined using the Borda count method and the logistic regression method. The results indicate that fusing individual modalities improve the overall performance of the biometric system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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