Publication Type : Conference Proceedings
Source : Imaging and Applied Optics Congress
Campus : Amaravati
School : School of Engineering
Year : 2022
Abstract : We developed a deep stacked undercomplete autoencoder (i.e., supervised) network to denoise the noisy 3D sectional images. Results demonstrate the feasibility of our proposed model in terms of peak-signal-to-noise ratio.
Cite this Research Publication : Vineela Chandra Dodda, Lakshmi Kuruguntla, Karthikeyan Elumalai, Inbarasan Muniraj, Sunil Chinnadurai, “An undercomplete autoencoder for denoising computational 3D sectional images”, Imaging and Applied Optics Congress, Canada, 2022.