Hyperspectral Image Classification with Optimized Compressed Synergic Deep Convolution Neural Network with Aquila Optimization

Table 2

HSI categorization for KSC dataset.

methods	RNN	DCNN	SDCNN	CSDCNN	CSDCNN-AO
OA	45.22 ± 0.45	47.89 ± 0.89	88.36 ± 1.13	87.48 ± 0.86	92.33 ± 1.08
AA	37.31 ± 1.06	56.60 ± 3.29	85.39 ± 1.17	82.43 ± 1.11	93.44 ± 1.82
K	52.97 ± 0.58	53.12 ± 1.03	91.62 ± 2.54	93.12 ± 0.26	97.22 ± 1.25
1	22.89 ± 1.09	30.33 ± 7.33	89.00 ± 1.03	29.21 ± 30.0	84.77 ± 11.6
2	44.46 ± 5.00	42.53 ± 3.04	86.35 ± 3.80	84.79 ± 0.26	92.38 ± 4.87
3	46.69 ± 2.61	53.91 ± 8.28	86.18 ± 7.24	85.93 ± 1.26	93.06 ± 4.53
4	29.79 ± 9.7	21.17 ± 3.25	84.17 ± 5.52	88.11 ± 1.12	95.84 ± 4.89
5	36.71 ± 6.67	68.79 ± 2.13	85.75 ± 2.55	87.28 ± 1.34	94.65 ± 1.95
6	88.57 ± 1.71	92.78 ± 0.78	88.08 ± 3.06	93.82 ± 0.32	95.95 ± 0.96
7	38.34 ± 11.4	20.85 ± 7.79	71.89 ± 29.45	42.69 ± 2.13	92.48 ± 24.0
8	91.46 ± 2.15	94.84 ± 3.15	91.25 ± 2.40	95.22 ± 0.31	97.11 ± 3.09
9	64.78 ± 19.04	0.00 ± 0.00	54.0 ± 49.0	32.00 ± 2.05	89.72 ± 8.38
10	61.46 ± 1.91	61.53 ± 1.24	89.47 ± 7.69	81.28 ± 0.89	98.40 ± 2.86
11	79.89 ± 2.49	66.88 ± 4.33	93.77 ± 5.03	95.85 ± 0.67	93.97 ± 3.29
12	47.14 ± 5.56	47.57 ± 3.85	77.97 ± 5.16	83.77 ± 4.37	95.89 ± 4.55
13	49.68 ± 7.17	87.02 ± 1.22	97.45 ± 5.29	79.86 ± 4.56	97.89 ± 0.87