Dutta, M.; Islam Sujan, M.R.; Mojumdar, M.U.; Chakraborty, N.R.; Marouf, A.A.; Rokne, J.G.; Alhajj, R.
Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2 Architectures. Technologies 2024, 12, 214.
https://doi.org/10.3390/technologies12110214
AMA Style
Dutta M, Islam Sujan MR, Mojumdar MU, Chakraborty NR, Marouf AA, Rokne JG, Alhajj R.
Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2 Architectures. Technologies. 2024; 12(11):214.
https://doi.org/10.3390/technologies12110214
Chicago/Turabian Style
Dutta, Monoronjon, Md Rashedul Islam Sujan, Mayen Uddin Mojumdar, Narayan Ranjan Chakraborty, Ahmed Al Marouf, Jon G. Rokne, and Reda Alhajj.
2024. "Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2 Architectures" Technologies 12, no. 11: 214.
https://doi.org/10.3390/technologies12110214
APA Style
Dutta, M., Islam Sujan, M. R., Mojumdar, M. U., Chakraborty, N. R., Marouf, A. A., Rokne, J. G., & Alhajj, R.
(2024). Rice Leaf Disease Classification—A Comparative Approach Using Convolutional Neural Network (CNN), Cascading Autoencoder with Attention Residual U-Net (CAAR-U-Net), and MobileNet-V2 Architectures. Technologies, 12(11), 214.
https://doi.org/10.3390/technologies12110214
