Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques

Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques

Abstract Wheat commands attention due to its significant impact on culture, nutrition, the economy, and the guarantee of food security. The anticipated rise in temperatures resulting from climate change is a key factor contributing to food insecurity, as it markedly reduces wheat harvests. Terminal...

Full description

Saved in:
Bibliographic Details
Main Authors: Arifa Zahir, Zulfiqar Ali, Ahmad Sami Al-Shamayleh, Syed Raza Ab bas, Basharat Mahmood, Abdullah Hussein Al-Ghushami, Rubina Adnan, Adnan Akhunzada
Format: Article
Language:English
Published: Nature Portfolio 2024-10-01
Series:Scientific Reports
Subjects:
Convolution neural network
LeNet
ResNet
Inception V3
Inception V4
Artificial Intelligence
Online Access:https://doi.org/10.1038/s41598-024-74875-7
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-024-74875-7

Similar Items