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. Author manuscript; available in PMC: 2023 Aug 1.
Published in final edited form as: J Biophotonics. 2022 Apr 20;15(8):e202200008. doi: 10.1002/jbio.202200008

TABLE 3.

[The mean average precision (mAP) of trained models on each image datasets using YOLOv5 and Faster RCNN. Red highlights indicate highest values within the model, as well as highlighting that YOLOv5 NIR has a higher mAP value than any Faster RCNN image type.]

Model Inference time, ms (1/FPS) Image Type mAP.5:.95
YOLOv5 19.5 ms
(1/51.28 FPS)
Dual 0.947
RGB 0.842
NIR 0.913
Faster RCNN 71.4 ms
(1/13.99 FPS)
Dual 0.898
RGB 0.742
NIR 0.856