1280 x 960 pixel microscanned infrared imaging module
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The needs of surveillance/detection operations in the infrared range, for industrial, spatial and military applications continuously tend toward larger field of view and resolution while maintaining the system as compact as possible. To answer this need, INO has developed a 1280x960 pixel thermal imager, said HRXCAM, with 22.6° field of view. This system consists in the assembly of a catadioptric optics with microscan mechanism and a detection electronic module based on a 640x480 25μm pitch pixel bolometric detector. The detection module, said IRXCAM, is a flexible platform developed for fast prototyping of varied systems thanks to its ability to support a large range of infrared detectors. With its multiple hardware and software functionalities, IRXCAM can also be used as the complete electronic module of a finalized system. HRXCAM is an example of fast prototyping with IRXCAM and an optical lens that fully demonstrates the imaging performance of the final system. HRXCAM provides 1280x960 pixel images at a nominal 5-15 Hz frequency with 60 mK NETD. It can also be used in the 640x480 mode at 58 Hz with the same sensitivity. In this paper, the catadioptric optics with integrated microscan and IRXCAM architecture and specifications are reviewed. Some typical examples of image obtained with HRXCAM in outdoor conditions are presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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