Home ›
Entities
› academia
› ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation
ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation
ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation is a scholarly article[1].
Key Facts
ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation. Retrieved October 18, 2026, from https://4ort.xyz/entity/ilgnet-inception-modules-with-connected-local-and-global-features-for-efficient-image-aesthetic-quality-classification-u
MLA“ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation.” 4ort.xyz Knowledge Graph, 4ort.xyz, 18 Oct. 2026, https://4ort.xyz/entity/ilgnet-inception-modules-with-connected-local-and-global-features-for-efficient-image-aesthetic-quality-classification-u.
BibTeX@misc{4ortxyz_ilgnet-inception-modules-with-connected-local-and-global-features-for-efficient-image-aesthetic-quality-classification-u_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation}}, year = {2026}, url = {https://4ort.xyz/entity/ilgnet-inception-modules-with-connected-local-and-global-features-for-efficient-image-aesthetic-quality-classification-u}, note = {Accessed: 2026-10-18}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): ILGNet: inception modules with connected local and global features for efficient image aesthetic quality classification using domain adaptation — https://4ort.xyz/entity/ilgnet-inception-modules-with-connected-local-and-global-features-for-efficient-image-aesthetic-quality-classification-u (retrieved 2026-10-18)
