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Table 3 The performances of the herbicide weed control spectrum neural networks for detecting and discriminating the sub-images containing weeds susceptible to ACCase-inhibiting herbicides, weeds susceptible to synthetic auxin herbicides, or bermudagrass turf exclusively (no herbicide)

From: Deep learning for detecting herbicide weed control spectrum in turfgrass

Deep learning architecture Herbicides Validation dataset Testing dataset
Precision Recall Overall accuracy F1 score Precision Recall Overall accuracy F1 score
GoogLeNet ACCase-inhibiting 0.995 0.999 0.998 0.997 0.993 0.999 0.997 0.996
Synthetic auxin 0.999 0.995 0.998 0.997 0.998 0.994 0.997 0.996
No herbicide 1.000 0.999 1.000 0.999 1.000 0.999 1.000 0.999
MobileNet-v3 ACCase-inhibiting 0.976 0.965 0.980 0.970 0.973 0.963 0.979 0.968
Synthetic auxin 0.978 0.978 0.985 0.978 0.981 0.971 0.984 0.976
No herbicide 0.971 0.983 0.985 0.977 0.965 0.985 0.983 0.975
ShuffleNet-v2 ACCase-inhibiting 1.000 1.000 1.000 1.000 1.000 0.999 1.000 0.999
Synthetic auxin 0.999 1.000 1.000 0.999 0.999 1.000 0.999 0.999
No herbicide 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
VGGNet ACCase-inhibiting 0.998 1.000 0.999 0.999 0.998 0.999 0.999 0.998
Synthetic auxin 1.000 1.000 1.000 1.000 0.998 1.000 0.999 0.999
No herbicide 1.000 0.998 0.999 0.999 1.000 0.997 0.999 0.998