Wireless Biometric Individual Identification Utilizing Millimeter Waves
Why this work is in the frame
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Bibliographic record
Abstract
Biometrics offer a personal and convenient way of keeping our identities and our data secure. Here, we introduce a method of using mm-wave sensors to identify various individuals. In our system prototype, the compact radar sensor has two transmit antennas and four receive ones. The transmitter(s) send a sequence of signals which are reflected and scattered from a nearby part of the body of a user (a hand in our demo case). Different signal processing algorithms are applied to the received signals in order to create a rich feature dataset. In our demo system, the resulting dataset is classified using a random forest machine learning model, which is shown to facilitate identifying a group of individuals with high accuracy. This technology has promising implications in terms of using mm-wave radars as an independent or an auxiliary tool for biometric authentication.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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