Modular infrared 640 x 480 pixel camera core for rapid device integration
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
In the observation and surveillance fields, there is an increasing demand for infrared modules that can be rapidly turned into a complete autonomous device whether it is for military, security or industrial purposes. Based on this concept, INO has developed a modular 16 bit infrared camera core. The tool can be used to provide a rapid evaluation of an application concept. Moreover, a complete device can be rapidly designed and build once the concept has been demonstrated. The IRXCore-640 camera core, integrating a 640 x 480 pixel uncooled FPA and providing a 16-bit raw signal output at 60 Hz, gives total access to the detector configuration parameters to ease developers integration process. TECless operation minimizes module size and power consumption. The camera core can be configured at the factory for outdoors operation from -30°C to +60°C with 200°C scene dynamic range at maximum sensitivity. The device can be used with refractive optics or catadioptric optical objectives. Windowing capability provides flexibility in frame frequency, sensitivity selection, and a choice of operating field of view. High resolution/high sensitivity can be achieved. In this paper, the camera core will be reviewed as well as its performances. The control software functionalities are detailed and some typical imaging examples will be 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 | 0.001 |
| 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 | 0.000 |
| 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