New concept for corrosion inspection of urban pipeline networks by digital image processing
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
Closed-circuit television (CCTV) is currently used in many inspection applications, such as the inspection of non accessible pipe surfaces. This human-oriented approach based on offline analysis of the raw images is highly subjective and prone to error because of the exorbitant amount of data to be assessed. This paper describes a methodology for automatic analysis of the inner surface of pipelines by means of digital image processing (DIP). The whole platform consists of an inspection mobile robot that carries a Line-Laser and a CCTV camera to recognize defects of the inner pipeline structure that is not easily accessible for human inspectors. A simple algorithm is presented that is able to detect cracks in the inner surface of the pipes with approximately 80 percent accuracy in final result, representing the main purpose of vision systems and the use of DIP technique. Experiments illustrate that the same set of results are achieved when the inner pipe is not illuminated.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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