Pointer-Type Dashboard Recognition Algorithm for Real-Time Detection——An Improved Method Based on YOLOv8
Why this work is in the frame
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Bibliographic record
Abstract
With the development of intelligent and automated technologies, pointer-type instruments are still widely used in various fields. To improve the recognition accuracy and real-time performance of pointer-type instruments, this paper proposes an improved algorithm based on YOLOv8. The algorithm integrates the DetectAFPN detection head and CGAttention attention mechanism into the original YOLOv8 architecture for optimization. By introducing the DetectAFPN detection head, the algorithm can more effectively handle features at different scales, while the CGAttention attention mechanism enhances the network's focus on important features, thus improving recognition accuracy. Additionally, this paper performs lightweight optimization on the original model, reducing computational resource consumption and improving real-time detection capability. Experimental results show that the improved model outperforms the traditional YOLOv8 in several metrics, achieving more accurate and efficient pointer-type instrument recognition.
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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 | 0.000 |
| 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