Improved Deep Convolutional Neural Network for Digital Art Image Classification and Identification Article Swipe

PDF

Huidong Zhang ·

YOU? · · 2025 · Open Access · · DOI: https://doi.org/10.1007/s44196-025-00996-0

In this paper, an enhanced deep convolutional neural network (DCNN) is proposed to address the challenges of accuracy and diversity in digital art image classification. This method significantly improves the feature extraction capability and model generalization performance by introducing an attention mechanism, residual connection and transfer learning. The key improvements include optimized network architecture, use of LeakyReLU activation function and fine-tuning of pre-trained models. Experimental results show that the improved DCNN performs significantly better than traditional DCNN on multiple datasets, especially when processing digital art images with complex styles and abstract forms the classification accuracy and generalization ability are significantly improved. In addition, the model also shows superiority in indicators such as specificity and Cohen's Kappa coefficient, which further verifies the effectiveness of the combination strategy. This enhanced DCNN not only has broad application prospects in the field of digital art but also provides a valuable reference for other image classification tasks.

Related Topics

Digital Footprint

Digital Art

Digital Media Use And Mental Health

The Amazing Digital Circus

The Social Network (Soundtrack)

Global Network

Neural Correlates Of Consciousness

Digital Services Tax Act (Canada)

Dominion Voting Systems V. Fox News Network

Virtual Private Network

Deep Vein Thrombosis

Concepts

No concepts available.

Metadata

Type: article
Language: en
Landing Page: https://doi.org/10.1007/s44196-025-00996-0
PDF: https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf
OA Status: gold
References: 18
OpenAlex ID: https://openalex.org/W4414850775

All OpenAlex metadata

Raw OpenAlex JSON

OpenAlex ID: https://openalex.org/W4414850775

Canonical identifier for this work in OpenAlex
DOI: https://doi.org/10.1007/s44196-025-00996-0

Digital Object Identifier
Title: Improved Deep Convolutional Neural Network for Digital Art Image Classification and Identification

Work title
Type: article

OpenAlex work type
Language: en

Primary language
Publication year: 2025

Year of publication
Publication date: 2025-10-06

Full publication date if available
Authors: Huidong Zhang

List of authors in order
Landing page: https://doi.org/10.1007/s44196-025-00996-0

Publisher landing page
PDF URL: https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf

Direct link to full text PDF
Open access: Yes

Whether a free full text is available
OA status: gold

Open access status per OpenAlex
OA URL: https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf

Direct OA link when available
Cited by: 0

Total citation count in OpenAlex
References (count): 18

Number of works referenced by this work

Full payload

id	https://openalex.org/W4414850775
doi	https://doi.org/10.1007/s44196-025-00996-0
ids.doi	https://doi.org/10.1007/s44196-025-00996-0
ids.openalex	https://openalex.org/W4414850775
fwci	0.0
type	article
title	Improved Deep Convolutional Neural Network for Digital Art Image Classification and Identification
biblio.issue	1
biblio.volume	18
biblio.last_page
biblio.first_page
topics[0].id	https://openalex.org/T12650
topics[0].field.id	https://openalex.org/fields/28
topics[0].field.display_name	Neuroscience
topics[0].score	0.9965999722480774
topics[0].domain.id	https://openalex.org/domains/1
topics[0].domain.display_name	Life Sciences
topics[0].subfield.id	https://openalex.org/subfields/2805
topics[0].subfield.display_name	Cognitive Neuroscience
topics[0].display_name	Aesthetic Perception and Analysis
topics[1].id	https://openalex.org/T10775
topics[1].field.id	https://openalex.org/fields/17
topics[1].field.display_name	Computer Science
topics[1].score	0.9879000186920166
topics[1].domain.id	https://openalex.org/domains/3
topics[1].domain.display_name	Physical Sciences
topics[1].subfield.id	https://openalex.org/subfields/1707
topics[1].subfield.display_name	Computer Vision and Pattern Recognition
topics[1].display_name	Generative Adversarial Networks and Image Synthesis
topics[2].id	https://openalex.org/T14254
topics[2].field.id	https://openalex.org/fields/17
topics[2].field.display_name	Computer Science
topics[2].score	0.973800003528595
topics[2].domain.id	https://openalex.org/domains/3
topics[2].domain.display_name	Physical Sciences
topics[2].subfield.id	https://openalex.org/subfields/1704
topics[2].subfield.display_name	Computer Graphics and Computer-Aided Design
topics[2].display_name	Digital Media and Visual Art
is_xpac	False
apc_list.value	1390
apc_list.currency	GBP
apc_list.value_usd	1704
apc_paid.value	1390
apc_paid.currency	GBP
apc_paid.value_usd	1704
language	en
locations[0].id	doi:10.1007/s44196-025-00996-0
locations[0].is_oa	True
locations[0].source.id	https://openalex.org/S190680769
locations[0].source.issn	1875-6883, 1875-6891
locations[0].source.type	journal
locations[0].source.is_oa	True
locations[0].source.issn_l	1875-6883
locations[0].source.is_core	True
locations[0].source.is_in_doaj	True
locations[0].source.display_name	International Journal of Computational Intelligence Systems
locations[0].source.host_organization	https://openalex.org/P4310319965
locations[0].source.host_organization_name	Springer Nature
locations[0].source.host_organization_lineage	https://openalex.org/P4310319965
locations[0].source.host_organization_lineage_names	Springer Nature
locations[0].license	cc-by-nc-nd
locations[0].pdf_url	https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf
locations[0].version	publishedVersion
locations[0].raw_type	journal-article
locations[0].license_id	https://openalex.org/licenses/cc-by-nc-nd
locations[0].is_accepted	True
locations[0].is_published	True
locations[0].raw_source_name	International Journal of Computational Intelligence Systems
locations[0].landing_page_url	https://doi.org/10.1007/s44196-025-00996-0
locations[1].id	pmh:oai:doaj.org/article:4d6a1e8fea5e4627a15074f298012e80
locations[1].is_oa	False
locations[1].source.id	https://openalex.org/S4306401280
locations[1].source.issn
locations[1].source.type	repository
locations[1].source.is_oa	False
locations[1].source.issn_l
locations[1].source.is_core	False
locations[1].source.is_in_doaj	False
locations[1].source.display_name	DOAJ (DOAJ: Directory of Open Access Journals)
locations[1].source.host_organization
locations[1].source.host_organization_name
locations[1].license
locations[1].pdf_url
locations[1].version	submittedVersion
locations[1].raw_type	article
locations[1].license_id
locations[1].is_accepted	False
locations[1].is_published	False
locations[1].raw_source_name	International Journal of Computational Intelligence Systems, Vol 18, Iss 1, Pp 1-17 (2025)
locations[1].landing_page_url	https://doaj.org/article/4d6a1e8fea5e4627a15074f298012e80
indexed_in	crossref, doaj
authorships[0].author.id	https://openalex.org/A5085322583
authorships[0].author.orcid	https://orcid.org/0000-0001-7845-3331
authorships[0].author.display_name	Huidong Zhang
authorships[0].author_position	first
authorships[0].raw_author_name	Huidong Zhang
authorships[0].is_corresponding	True
has_content.pdf	True
has_content.grobid_xml	False
is_paratext	False
open_access.is_oa	True
open_access.oa_url	https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf
open_access.oa_status	gold
open_access.any_repository_has_fulltext	False
created_date	2025-10-10T00:00:00
display_name	Improved Deep Convolutional Neural Network for Digital Art Image Classification and Identification
has_fulltext	False
is_retracted	False
updated_date	2025-11-06T03:46:38.306776
primary_topic.id	https://openalex.org/T12650
primary_topic.field.id	https://openalex.org/fields/28
primary_topic.field.display_name	Neuroscience
primary_topic.score	0.9965999722480774
primary_topic.domain.id	https://openalex.org/domains/1
primary_topic.domain.display_name	Life Sciences
primary_topic.subfield.id	https://openalex.org/subfields/2805
primary_topic.subfield.display_name	Cognitive Neuroscience
primary_topic.display_name	Aesthetic Perception and Analysis
cited_by_count	0
locations_count	2
best_oa_location.id	doi:10.1007/s44196-025-00996-0
best_oa_location.is_oa	True
best_oa_location.source.id	https://openalex.org/S190680769
best_oa_location.source.issn	1875-6883, 1875-6891
best_oa_location.source.type	journal
best_oa_location.source.is_oa	True
best_oa_location.source.issn_l	1875-6883
best_oa_location.source.is_core	True
best_oa_location.source.is_in_doaj	True
best_oa_location.source.display_name	International Journal of Computational Intelligence Systems
best_oa_location.source.host_organization	https://openalex.org/P4310319965
best_oa_location.source.host_organization_name	Springer Nature
best_oa_location.source.host_organization_lineage	https://openalex.org/P4310319965
best_oa_location.source.host_organization_lineage_names	Springer Nature
best_oa_location.license	cc-by-nc-nd
best_oa_location.pdf_url	https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf
best_oa_location.version	publishedVersion
best_oa_location.raw_type	journal-article
best_oa_location.license_id	https://openalex.org/licenses/cc-by-nc-nd
best_oa_location.is_accepted	True
best_oa_location.is_published	True
best_oa_location.raw_source_name	International Journal of Computational Intelligence Systems
best_oa_location.landing_page_url	https://doi.org/10.1007/s44196-025-00996-0
primary_location.id	doi:10.1007/s44196-025-00996-0
primary_location.is_oa	True
primary_location.source.id	https://openalex.org/S190680769
primary_location.source.issn	1875-6883, 1875-6891
primary_location.source.type	journal
primary_location.source.is_oa	True
primary_location.source.issn_l	1875-6883
primary_location.source.is_core	True
primary_location.source.is_in_doaj	True
primary_location.source.display_name	International Journal of Computational Intelligence Systems
primary_location.source.host_organization	https://openalex.org/P4310319965
primary_location.source.host_organization_name	Springer Nature
primary_location.source.host_organization_lineage	https://openalex.org/P4310319965
primary_location.source.host_organization_lineage_names	Springer Nature
primary_location.license	cc-by-nc-nd
primary_location.pdf_url	https://link.springer.com/content/pdf/10.1007/s44196-025-00996-0.pdf
primary_location.version	publishedVersion
primary_location.raw_type	journal-article
primary_location.license_id	https://openalex.org/licenses/cc-by-nc-nd
primary_location.is_accepted	True
primary_location.is_published	True
primary_location.raw_source_name	International Journal of Computational Intelligence Systems
primary_location.landing_page_url	https://doi.org/10.1007/s44196-025-00996-0
publication_date	2025-10-06
publication_year	2025
referenced_works	https://openalex.org/W3092897249, https://openalex.org/W4296177544, https://openalex.org/W4294542659, https://openalex.org/W4389823430, https://openalex.org/W2572559801, https://openalex.org/W3189728456, https://openalex.org/W4392567285, https://openalex.org/W4400482068, https://openalex.org/W4389264040, https://openalex.org/W2996367417, https://openalex.org/W2884675507, https://openalex.org/W3168997536, https://openalex.org/W3004895274, https://openalex.org/W4293527381, https://openalex.org/W4296690332, https://openalex.org/W4381891014, https://openalex.org/W4389263866, https://openalex.org/W4237781669
referenced_works_count	18
abstract_inverted_index.a	145
abstract_inverted_index.In	1, 102
abstract_inverted_index.an	4, 40
abstract_inverted_index.as	112
abstract_inverted_index.by	38
abstract_inverted_index.in	21, 109, 136
abstract_inverted_index.is	11
abstract_inverted_index.of	17, 56, 62, 123, 139
abstract_inverted_index.on	78
abstract_inverted_index.to	13
abstract_inverted_index.The	48
abstract_inverted_index.and	19, 34, 45, 60, 90, 96, 114
abstract_inverted_index.are	99
abstract_inverted_index.art	23, 85, 141
abstract_inverted_index.but	142
abstract_inverted_index.for	148
abstract_inverted_index.has	132
abstract_inverted_index.key	49
abstract_inverted_index.not	130
abstract_inverted_index.the	15, 30, 69, 93, 104, 121, 124, 137
abstract_inverted_index.use	55
abstract_inverted_index.DCNN	71, 77, 129
abstract_inverted_index.This	26, 127
abstract_inverted_index.also	106, 143
abstract_inverted_index.deep	6
abstract_inverted_index.only	131
abstract_inverted_index.show	67
abstract_inverted_index.such	111
abstract_inverted_index.than	75
abstract_inverted_index.that	68
abstract_inverted_index.this	2
abstract_inverted_index.when	82
abstract_inverted_index.with	87
abstract_inverted_index.Kappa	116
abstract_inverted_index.broad	133
abstract_inverted_index.field	138
abstract_inverted_index.forms	92
abstract_inverted_index.image	24, 150
abstract_inverted_index.model	35, 105
abstract_inverted_index.other	149
abstract_inverted_index.shows	107
abstract_inverted_index.which	118
abstract_inverted_index.(DCNN)	10
abstract_inverted_index.better	74
abstract_inverted_index.images	86
abstract_inverted_index.method	27
abstract_inverted_index.neural	8
abstract_inverted_index.paper,	3
abstract_inverted_index.styles	89
abstract_inverted_index.tasks.	152
abstract_inverted_index.Cohen's	115
abstract_inverted_index.ability	98
abstract_inverted_index.address	14
abstract_inverted_index.complex	88
abstract_inverted_index.digital	22, 84, 140
abstract_inverted_index.feature	31
abstract_inverted_index.further	119
abstract_inverted_index.include	51
abstract_inverted_index.models.	64
abstract_inverted_index.network	9, 53
abstract_inverted_index.results	66
abstract_inverted_index.Abstract	0
abstract_inverted_index.abstract	91
abstract_inverted_index.accuracy	18, 95
abstract_inverted_index.enhanced	5, 128
abstract_inverted_index.function	59
abstract_inverted_index.improved	70
abstract_inverted_index.improves	29
abstract_inverted_index.multiple	79
abstract_inverted_index.performs	72
abstract_inverted_index.proposed	12
abstract_inverted_index.provides	144
abstract_inverted_index.residual	43
abstract_inverted_index.transfer	46
abstract_inverted_index.valuable	146
abstract_inverted_index.verifies	120
abstract_inverted_index.LeakyReLU	57
abstract_inverted_index.addition,	103
abstract_inverted_index.attention	41
abstract_inverted_index.datasets,	80
abstract_inverted_index.diversity	20
abstract_inverted_index.improved.	101
abstract_inverted_index.learning.	47
abstract_inverted_index.optimized	52
abstract_inverted_index.prospects	135
abstract_inverted_index.reference	147
abstract_inverted_index.strategy.	126
abstract_inverted_index.activation	58
abstract_inverted_index.capability	33
abstract_inverted_index.challenges	16
abstract_inverted_index.connection	44
abstract_inverted_index.especially	81
abstract_inverted_index.extraction	32
abstract_inverted_index.indicators	110
abstract_inverted_index.mechanism,	42
abstract_inverted_index.processing	83
abstract_inverted_index.application	134
abstract_inverted_index.combination	125
abstract_inverted_index.fine-tuning	61
abstract_inverted_index.introducing	39
abstract_inverted_index.performance	37
abstract_inverted_index.pre-trained	63
abstract_inverted_index.specificity	113
abstract_inverted_index.superiority	108
abstract_inverted_index.traditional	76
abstract_inverted_index.Experimental	65
abstract_inverted_index.coefficient,	117
abstract_inverted_index.improvements	50
abstract_inverted_index.architecture,	54
abstract_inverted_index.convolutional	7
abstract_inverted_index.effectiveness	122
abstract_inverted_index.significantly	28, 73, 100
abstract_inverted_index.classification	94, 151
abstract_inverted_index.generalization	36, 97
abstract_inverted_index.classification.	25
cited_by_percentile_year
corresponding_author_ids	https://openalex.org/A5085322583
countries_distinct_count	0
institutions_distinct_count	1
citation_normalized_percentile.value	0.49374571
citation_normalized_percentile.is_in_top_1_percent	False
citation_normalized_percentile.is_in_top_10_percent	False