Deep Learning Modeling and Visual Aesthetics Integration Path in Cultural and Creative Designs

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Visual evaluation factor score

	AVQ	Naturality	Diversity	Coordination	Peculiarity	Ordinal	Animality	Culture	Innovation
Figure 1	7.15	6.14	4.61	6.85	3.71	5.29	6.48	5.38	5.8
Figure 2	6.34	6.52	5.49	6.73	4.71	5	6.72	7.41	7.77
Figure 3	6.05	3.81	5.41	6.14	5.23	4.71	6.41	3.6	7.26
Figure 4	5.83	5.92	6.1	7.51	4.29	5.76	6.6	8.24	6.29
Figure 5	6	2.92	5.33	7.75	4.74	5.91	6.35	7.63	7.49
Figure 6	7	7.77	3.42	6.24	5.79	7.13	5.68	8.32	7.47
Figure 7	6.95	6.74	3.9	6.9	4.34	7.32	5.73	4	7.63
Figure 8	6.02	4.51	6.18	6.58	3.89	6.2	7	8.46	6
Figure 9	6.59	4.41	3.39	7.67	4.56	7.35	5.93	5.44	5.6
Figure 10	5.83	4.07	4.76	7.62	5.59	5.41	5.91	6.83	7.43
Figure 11	5.75	6.26	5.62	6.07	6.1	5.8	6.96	4.68	5.99
Figure 12	6.8	8.6	5.25	5.98	4.08	6.18	6.16	8.11	7.03

The correlation between the visual and semantic variables

	Naturality	Diversity	Coordination	Peculiarity	Ordinal	Animality	Culture	Innovation	AVQ
Naturality	1
Diversity	0.512	1
Coordination	0.446	0.287	1
Peculiarity	-0.836**	-0.215	-0.175	1
Ordinal	-0.466	-0.168	0.524	0.63	1
Animality	0.295	0.836**	0.325	-0.069	-0.096	1
Culture	-0.988**	-0.485	-0.378	0.765**	0.524	-0.269	1
Innovation	0.002	0.078	0.825**	0.112	0.689*	0.352	0.095	1
AVQ	-0.155	0.172	0.736**	0.458	0.845**	0.351	0.215	0.836**	1

“Implicit” image evaluation regression analysis results

Scheme	Regression coefficient	The regression coefficient confidence interval	Residual error	Residual confidence interval	Correlation coefficient R2	F value	The probability of F corresponds to p	Error variance
1	0.39	[-0.89,1.5]	0.059	[-0.16,0.25]	0.78	23.25	0.012	0.006
2			0.032	[-0.22,0.31]
3	0.3	[-0.25,0.85]	-0.06	[-0.24,0.06]
4			0.01	[-0.24,0.24]
5	0.05	[-1.68,1.85]	-0.06	[-0.26,0.18]
6			-0.02	[-0.05,0.05]

Color beauty calculation results

Scheme	Color value(HSV)	Color design order sense	Total color number	Chromatic aberration	Brightness difference	Purity difference	Color beauty
1	(8,16,20),(187,98,50)	5.73	1.15	1	1	1	2
2	(198,100,91),(252,11,90),(15,5,28),(14,84,91)	17.28	0.96	6	6	5	1
3	(316,75,67),(0,83,90),(63,99,87),(240,53,60)	19.17	1.01	6	6	6	1
4	(146,89,55),(51,97,100),(19,18,54),(198,100,91)	16.43	0.86	6	6	6	1
5	(358,71,64),(149,87,50),(15,5,28)	14.17	1.77	3	1	3	1
6	(39,94,96),(88,72,75),(286,58,56)	9.29	0.93	3	3	3	1

“Generous” image evaluation regression analysis results

Scheme	Regression coefficient	The regression coefficient confidence interval	Residual error	Residual confidence interval	Correlation coefficient R2	F value	The probability of F corresponds to p	Error variance
1	0.089	[-0.45,0.59]	0.0032	[-0.13,0.15]	0.92	36.51	0.005	8.36x10-4
2			0.0395	[0.05,0.09]
3	0.63	[0.22,0.69]	-0.0239	[-0.15,0.08]
4			-0.0165	[-0.15,0.09]
5	0.25	[-0.65,0.89]	-0.0031	[-0.1,0.2]
6			2.86 x10-4	[-0.05,0.05]

User evaluation data anti-fuzzy processing

Imagery	1	2	3	4	5	6
Generous	0.802	0.651	0.615	0.558	0.824	0.599
Connotation	0.827	0.694	0.612	0.665	0.752	0.636
Comprehensive evaluation	0.815	0.673	0.614	0.612	0.788	0.618

The vision of the color scheme is calculated

Scheme number	Symmetry	Equalization	Proportionality	Mean
1	0.8658	0.8537	0.9345	0.8876
2	0.7942	0.761	0.8257	0.7903
3	0.7942	0.761	0.8257	0.7903
4	0.7942	0.761	0.8257	0.7903
5	0.8967	0.8882	0.9493	0.9093
6	0.8967	0.8882	0.9493	0.9093