Table 11 ANOVA on RMSE of various model
From: GrainNet: efficient detection and counting of wheat grains based on an improved YOLOv7 modeling
(a)Input summary | ||||||
|---|---|---|---|---|---|---|
Model | Count | Mean | Std | 95% CI | ||
GrainNet | 5 | 20.53126 | 5.41103 | (15.78828, 25.27423) | ||
YOLOv7 | 5 | 30.14253 | 4.71887 | (26.00625, 34.27880) | ||
YOLOv8 | 5 | 23.19211 | 4.15189 | (19.55282, 26.83140) | ||
FasterRCNN | 5 | 57.94406 | 7.60620 | (51.27693, 64.61119) | ||
YOLOv5 | 5 | 21.38524 | 1.63922 | (19.94841, 22.82208) | ||
(b)ANOVA result | ||||||
|---|---|---|---|---|---|---|
Source of Variation | SS | df | MS | F Stat | P-value | F crit |
Between Groups | 4945.33610 | 4 | 1236.33402 | 38.23916 | 4.20808E-09 | 2.86608 |
Within Groups | 646.63247 | 20 | 32.33162 | - | - | - |
Total | 5591.96856 | 24 | - | - | - | - |
(c)Post Hoc Analysis | Â | |||||
|---|---|---|---|---|---|---|
Model compared with GrainNet | Difference of means | LSD | Lower-bound | Upper-Bound | Â | |
YOLOv7 | -9.61127 | 61.74290 | -71.35417 | 52.13162 | Â | |
YOLOv8 | -2.66085 | 61.74290 | -64.40375 | 59.08204 | Â | |
FasterRCNN | -37.41280 | 61.74290 | -99.15570 | 24.33010 | Â | |
YOLOv5 | -0.85399 | 61.74290 | -62.59689 | 60.88891 | Â | |