Flexible 640 x 480 pixel infrared camera module for fast prototyping
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 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.
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