FIGURE
Fig 5
- ID
- ZDB-FIG-211207-35
- Publication
- Albuquerque et al., 2021 - Object detection for automatic cancer cell counting in zebrafish xenografts
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Fig 5
Performance comparison using the mAP of the object-detection models trained using various meta-architectures (Faster R-CNN, SSD, YOLO and RFCN) for 4,000 steps.
Faster algorithms such as SSD cannot deal with the complexity of the problem. Faster R-CNN emphasizes accuracy over speed and can achieve over six times better performance than SSD with the same feature extractor. YOLO v5, the last version of YOLO, outperforms SSD and RFCN, but Faster R-CNN still has an advantage of 0.1 mAP at 4,000 steps. |
Expression Data
Expression Detail
Antibody Labeling
Phenotype Data
Phenotype Detail
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