On the public citation graph

Machine Learning Approach on AI Painter: Chinese Traditional Painting Classification and Creation

https://doi.org/10.2139/ssrn.4267779
0 signed · 5 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s12144-025-07968-9openalex-snapshot
Stress relief through tradition: the psychological restoration effect of AI vs. human-created cultural videos
inferred← citeshttps://doi.org/10.1007/s13198-026-03344-3openalex-snapshot
On the application of machine learning techniques for quality assurance in an automobile paint shop
inferred← citeshttps://doi.org/10.1142/s0218488524400154openalex-snapshot
A Multi-Branch Residual Network Based on Depth Correlation Features for the Classification of Chinese Ink Paintings
inferred← citeshttps://doi.org/10.1145/3689641openalex-snapshot
Revolutionizing Visuals: The Role of Generative AI in Modern Image Generation
inferred← citeshttps://doi.org/10.1145/3769526.3769626openalex-snapshot
Hybrid Workflow in AI-Driven Stylisation and Hand-Drawn Animation
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.