Using Deep Convolutional Neural Networks for Image-Based Diagnosis of Nutrient Deficiencies in Rice

Table 6

Recall, precision, and f1-score per class of nutrient deficiency for DenseNet121.

Class	Recall	Precision	f1	Samples
Full	0.96	0.90	0.93	58
−N	0.98	1.00	0.99	92
−P	1.00	0.97	0.98	61
−K	0.98	1.00	0.99	43
−Ca	0.95	0.95	0.95	42
−Mg	1.00	1.00	1.00	43
−S	1.00	1.00	1.00	78
−Mn	0.98	0.96	0.97	104
−Fe	0.83	0.94	0.88	31
−Zn	0.97	0.96	0.97	112
−Si	0.97	1.00	0.98	64