<title>Image indexing in the JPEG2000 framework</title>
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
The application of images and video has increased significantly in recent years. It is crucial to develop indexing techniques for searching images and video based on their content. Recently, several indexing techniques have been proposed in both pixel and compressed domain. Due to its lower computational complexity, compressed domain indexing techniques are becoming popular. Among the compression techniques, discrete-wavelet-transform based techniques have become popular because of its excellent energy compaction and multi-resolution capability. The upcoming JPEG2000 image compression standard is also based on a wavelet coder. In this paper, a progressive bit-plane indexing scheme in the JPEG2000 framework is proposed. Here, a 2D significant0bit- map array and a 2D histogram of significant bits of wavelet coefficients are used as the image indices. Image retrieval is performed by matching the index of the query and candidate images from the database. Experimental results show that the proposed scheme provides a good indexing performance.
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 | 0.000 |
| 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