1 RESTITUTION OF INFORMATION UNDER SHADOW IN REMOTE SENSING HIGH SPACE RESOLUTION IMAGES: APPLICATION TO IKONOS DATA OF SHERBROOKE CITY
Why this work is in the frame
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Bibliographic record
Abstract
Shades have negative effects. They strongly disturb the classical techniques of image analysis by modifying surface appearance and sometimes involve loss of information under the surface they covered. In this study, we try to restore the information masked under the shadow by finding the types of surface covered by the shade. This search is based on the analysis of contextual, spectral and textural information from the shadow and its vicinity.This restitution supposes that shades are well identified, which was the aim of our former work. It takes into account the space configuration of the vicinity between the objects located sun side and surfaces in shade side which are supposed to receive the shadow. The application on an IKONOS image of Sherbrooke show that it is indeed possible to restore the information laying under the shadow and even discriminate several types of surface under the same shade, such as shades of buildings which are projected at the same time on grass, a portion of parking or on another building. The method also makes it possible to correct the shadow effects on the images. 1.
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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