Lock-in thermography using a cellphone attachment infrared camera
Bibliographic record
Abstract
Lock-in thermography (LIT) is a thermal-wave-based, non-destructive testing, technique which has been widely utilized in research settings for characterization and evaluation of biological and industrial materials. However, despite promising research outcomes, the wide spread adaptation of LIT in industry, and its commercialization, is hindered by the high cost of the infrared cameras used in the LIT setups. In this paper, we report on the feasibility of using inexpensive cellphone attachment infrared cameras for performing LIT. While the cost of such cameras is over two orders of magnitude less than their research-grade counterparts, our experimental results on block sample with subsurface defects and tooth with early dental caries suggest that acceptable performance can be achieved through careful instrumentation and implementation of proper data acquisition and image processing steps. We anticipate this study to pave the way for development of low-cost thermography systems and their commercialization as inexpensive tools for non-destructive testing of industrial samples as well as affordable clinical devices for diagnostic imaging of biological tissues.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".