Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance

Mehta, Shiva; Kukreja, Vinay; Yadav, Rishika

doi:10.1109/icaiss58487.2023.10250461

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Multi-Classification of Heritage Buildings using Federated Learning CNN: A Comparative Analysis of Client-Side and Global Model Performance

Cited by 9 publications

References 14 publications

Advancements in machine visions for fruit sorting and grading: A bibliometric analysis, systematic review, and future research directions

Advancements in machine visions for fruit sorting and grading: A bibliometric analysis, systematic review, and future research directions

Advancing Table Tennis Analytics: A CNN-LSTM Framework for Precision Serve Shot Analysis

Revolutionizing Archaeological Discoveries: The Role of Artificial Intelligence and Machine Learning in Site Analysis

Contact Info

Product

Resources

About