Edge Prior Multilayer Segmentation Network Based on Bayesian Framework

Table 2

Confusion matrix of data set 2.

Method	Category	Others	Shrub	Higher crop	Untilled glebe	Building	Forest	Average acc.
FCN8	Others	81.62	1.86	4.76	6.82	2.10	2.84	75.34
	Shrub	33.45	65.23	0.87	0.12	0.19	0.14
	Higher crop	47.69	1.17	43.98	4.85	1.42	0.90
	Untilled glebe	11.88	0.09	2.72	82.89	1.45	0.97
	Building	34.69	0.36	1.54	1.80	44.92	16.68
	Forest	9.06	0.75	0.43	0.73	7.74	81.29
DeepLab	Others	73.29	0.76	25.85	0.02	0.06	0.01	78.83
	Shrub	1.29	49.23	41.26	2.15	5.07	1.01
	Higher crop	2.33	3.92	81.26	2.57	7.49	2.44
	Untilled glebe	0.03	0.72	19.81	69.94	1.26	8.23
	Building	0.15	1.16	10.73	2.34	84.60	1.02
	Forest	0.07	0.22	4.75	5.33	0.62	89.00
FCN8+DT+the fully connected CRF	Others	82.77	1.49	2.76	7.28	3.23	2.47	79.48
	Shrub	25.03	74.71	0.14	0.06	0.03	0.02
	Higher crop	39.64	0.94	52.88	3.29	2.23	1.03
	Untilled glebe	13.56	0.13	0.80	82.37	2.11	1.01
	Building	26.19	0.31	0.14	0.48	69.91	2.97
	Forest	10.04	0.08	0.04	0.27	3.56	86.01
FCN8+HED+DT+the fully connected CRF	Others	84.56	0.75	2.40	6.45	2.85	2.99	80.73
	Shrub	24.68	74.72	0.22	0.26	0.09	0.03
	Higher crop	39.16	0.55	53.20	3.88	2.21	1.00
	Untilled glebe	14.01	0.14	0.75	81.93	2.19	0.98
	Building	23.47	0.16	0.20	0.38	73.23	2.57
	Forest	9.58	0.09	0.06	0.26	3.58	86.43
Pro. approach	Others	86.90	0.39	1.63	6.96	2.21	1.90	82.54
	Shrub	30.82	69.00	0.17	0	0	0
	Higher crop	40.44	0.11	53.11	3.37	2.25	0.71
	Untilled glebe	10.08	0.07	0.65	85.92	2.48	0.80
	Building	16.63	0.03	0.10	0.47	80.68	2.09
	Forest	4.97	0.08	0.03	0.29	8.04	86.58