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

Mehdi Neshat

Showing results (1-10 of 4) with videos related to

Pageof 1
Sort By:
Sensors (Basel, Switzerland)|December 23, 2022
A Novel Hybrid Multi-Modal Deep Learning for Detecting Hashtag Incongruity on Social MediaSajad Dadgar, Mehdi Neshat
Australian and New Zealand Journal of Public Health|January 8, 2026
Two decades of climate change and its impact on emergency department presentations in the Australian Capital Territory: Past trend and future projectionMichael Tong, Nicole Vargas, Nikhil Jha, et al.
Scientific Reports|July 2, 2025
Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuningAmin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, et al.
Frontiers in Genetics|June 26, 2023
An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluationMehdi Neshat, Soohyun Lee, Md Moksedul Momin, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
Sensors (Basel, Switzerland)|December 23, 2022
A Novel Hybrid Multi-Modal Deep Learning for Detecting Hashtag Incongruity on Social MediaSajad Dadgar, Mehdi Neshat
Australian and New Zealand Journal of Public Health|January 8, 2026
Two decades of climate change and its impact on emergency department presentations in the Australian Capital Territory: Past trend and future projectionMichael Tong, Nicole Vargas, Nikhil Jha, et al.
Scientific Reports|July 2, 2025
Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuningAmin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, et al.
Frontiers in Genetics|June 26, 2023
An effective hyper-parameter can increase the prediction accuracy in a single-step genetic evaluationMehdi Neshat, Soohyun Lee, Md Moksedul Momin, et al.
Pageof 1