[Retracted] Correlation Analysis between the Emotion and Aesthetics for Chinese Classical Garden Design Based on Deep Transfer Learning

Table 1

Performance of Transfer-Inception V3, Inception V3, and VGG in terms of accuracy.

Iterations	Transfer-Inception V3	Inception V3	VGG
1	0.6274	0.4678	0.3024
10	0.8345	0.8071	0.6328
20	0.8642	0.8075	0.7896
30	0.8971	0.8367	0.8444
40	0.9111	0.8487	0.8621
50	0.9261	0.8610	0.8569
60	0.9220	0.8887	0.8675
70	0.9421	0.8700	0.8721
80	0.9356	0.8804	0.9008
90	0.9567	0.8675	0.9141
100	0.9587	0.8976	0.9120
110	0.9614	0.9172	0.9170
120	0.9681	0.9150	0.9155
130	0.9682	0.9231	0.9289
140	0.9675	0.9247	0.9394
150	0.9876	0.9227	0.9321
160	0.9814	0.9234	0.9346
170	0.9811	0.9112	0.9345
180	0.9781	0.9243	0.9238
190	0.9872	0.9231	0.9452
200	0.9786	0.9231	0.9511