Flexible 640 x 480 pixel infrared camera module for fast prototyping
Bibliographic record
Abstract
In various military, space and civilian infrared-based applications, there is an important need for fast prototyping. At the very heart, stands a requirement for flexible camera modules that provides a multitude of output formats as well as fast adaptability. Based on this concept, INO has developed an advanced compact camera module that can provide both raw data output as well as fully processed images under a variety of formats such as NTSC, PAL, VGA and GigE. This tool can be used to perform a rapid demonstration of an application concept. The IRXCam-640 camera core is a very flexible module that is based on a 640 x 480 pixels uncooled FPA but which may be rapidly modified to accommodate for other resolutions and sensor types. Providing 16-bit raw signal and 8-bit final image outputs at 60 Hz, the electronics gives total access to the detector configuration parameters. The output is available in NTSC, PAL, and GigE. An additional VGA output can be used as input for a microdisplay. TECless operation minimizes module size and power consumption. If required for absolute measurements, a TEC integrated to the detector package can be controlled with external electronics. The camera core can be configured for outdoors operation from -30°C to +60°C with 200°C scene dynamic range at maximum sensitivity. Windowing capability provides flexibility of frame frequency and operating field of view. The camera can be further coupled with a microscan mechanism to provide a high resolution 1280 x 960 pixel image. In this paper, the camera module is reviewed as well as its performances.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.008 |
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".