Semi-supervised deep learning of brain tissue segmentation

R Ito, K Nakae, J Hata, H Okano, S Ishii - Neural Networks, 2019 - Elsevier
Brain image segmentation is of great importance not only for clinical use but also for
neuroscience research. Recent developments in deep neural networks (DNNs) have led to …

Direct quantification of epistemic and aleatoric uncertainty in 3D U-net segmentation

CK Jones, G Wang, V Yedavalli… - Journal of Medical …, 2022 - spiedigitallibrary.org
Purpose: To derive a multinomial probability function and quantitative measures of the data
and epistemic uncertainty as direct output of a 3D U-Net segmentation network. Approach: A …

Speaker identification using convolutional neural network for clean and noisy speech samples

AM Jalil, FS Hasan, HA Alabbasi - 2019 first international …, 2019 - ieeexplore.ieee.org
Conventional speaker identification systems require features that are carefully designed to
achieve high identification accuracy rates. With deep learning, these features are learned …

Quantifying epistemic and aleatoric uncertainty in 3d u-net segmentation

CK Jones, G Wang, V Yedavalli, H Sair - medRxiv, 2021 - medrxiv.org
This work shows a derivation of a multinomial probability function and quantitative measures
of the data and epistemic uncertainty as direct output of a 3D U-Net segmentation network. A …

[PDF][PDF] 딥러닝을이용한뇌자기공명영상의정량분석기법

SJ Park, GH Jeong, U Sim, SJ Kim - Communications of the …, 2017 - koreascience.kr
이 있는데, 질병의 초력을 담당하는 주요 뇌 부위인 해마 (Hippocampus) 2 U| Z|||| II]](Entorhinal
cortext)-위에 뇌위축이 관찰되지만, 점차 두정엽, 전두엽등을거쳐 뇌전체로 퍼져 나간다. 이러한 …

[引用][C] Melon yield estimation using UAV images and deep learning

A Kalantar - 2019 - Ben-Gurion University of the Negev