Counting Methods
KNN and IOU based verification
Introduced by Alam et al. in Machine learning approach of automatic identification and counting of blood cellsKNN and IoU-based Verification is used to verify detections and choose between multiple detections of the same underlying object. It was originally used within the context of blood cell counting in medical images. To avoid this double counting problem, the KNN algorithm is applied in each platelet to determine its closest platelet and then using the intersection of union (IOU) between two platelets we calculate their extent of overlap. The authors allow 10% of the overlap between platelet and its closest platelet based on empirical observations. If the overlap is larger than that, they ignore that cell as a double count to get rid of spurious counting.
Source: Machine learning approach of automatic identification and counting of blood cells
Papers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| BIG-bench Machine Learning | 1 | 16.67% |
| Blood Cell Count | 1 | 16.67% |
| Blood Cell Detection | 1 | 16.67% |
| CBC TEST | 1 | 16.67% |
| Medical Diagnosis | 1 | 16.67% |
| Object Detection | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
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|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
