Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Jayaprakash Chinnadurai

Showing results (1-10 of 2) with videos related to

Pageof 1
Sort By:
Scientific Reports|August 15, 2025
Robust multiclass classification of crop leaf diseases using hybrid deep learning and Grad-CAM interpretabilitySankar Murugesan, Jayaprakash Chinnadurai, Saravanan Srinivasan, et al.
Scientific Reports|June 18, 2026
PI-HydroGNN: a physics-informed spatiotemporal graph neural network framework for hydraulic reliability, leakage detection, and energy-efficient operation in water distribution systemsJayaprakash Chinnadurai, KarthiPrem S, Sangeetha Ramaswamy, et al.
Pageof 1

Showing results (1-10 of 2) with videos related to

Sort By:
Pageof 1
Scientific Reports|August 15, 2025
Robust multiclass classification of crop leaf diseases using hybrid deep learning and Grad-CAM interpretabilitySankar Murugesan, Jayaprakash Chinnadurai, Saravanan Srinivasan, et al.
Scientific Reports|June 18, 2026
PI-HydroGNN: a physics-informed spatiotemporal graph neural network framework for hydraulic reliability, leakage detection, and energy-efficient operation in water distribution systemsJayaprakash Chinnadurai, KarthiPrem S, Sangeetha Ramaswamy, et al.
Pageof 1