Home ›
Entities
› academia
› Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance
Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance
Research article (2023 Second International Conference on Augmented Intelligence and Sustainable Systems (ICAISS), 2023) · cited 19× · AI/ML
Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance
Summary
Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance is a scholarly article[1].
Key Facts
Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance'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). Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance. Retrieved May 24, 2026, from https://4ort.xyz/entity/multi-classification-of-heritage-buildings-using-federated-learning-cnn-a-comparative-analysis-of-client-side-and-global
MLA“Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/multi-classification-of-heritage-buildings-using-federated-learning-cnn-a-comparative-analysis-of-client-side-and-global.
BibTeX@misc{4ortxyz_multi-classification-of-heritage-buildings-using-federated-learning-cnn-a-comparative-analysis-of-client-side-and-global_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance}}, year = {2026}, url = {https://4ort.xyz/entity/multi-classification-of-heritage-buildings-using-federated-learning-cnn-a-comparative-analysis-of-client-side-and-global}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance — https://4ort.xyz/entity/multi-classification-of-heritage-buildings-using-federated-learning-cnn-a-comparative-analysis-of-client-side-and-global (retrieved 2026-05-24)
