no code implementations • 21 Feb 2023 • Kanggeun Lee, Kyungryun Lee, Won-Ki Jeong
Although the advances of self-supervised blind denoising are significantly superior to conventional approaches without clean supervision in synthetic noise scenarios, it shows poor quality in real-world images due to spatially correlated noise corruption.
no code implementations • 3 Sep 2021 • Junyoung Choi, Hakjun Lee, Suyeon Kim, Seok-Kyu Kwon, Won-Ki Jeong
It is known that the morphology of mitochondria is closely related to the functions of neurons and neurodegenerative diseases.
no code implementations • CVPR 2021 • Tran Anh Tuan, Nguyen Tuan Khoa, Tran Minh Quan, Won-Ki Jeong
Instance segmentation, the task of identifying and separating each individual object of interest in the image, is one of the actively studied research topics in computer vision.
no code implementations • 10 Jun 2021 • Khoa Tuan Nguyen, Ganghee Jang, Tran Anh Tuan, Won-Ki Jeong
Segmentation of nanoscale electron microscopy (EM) images is crucial but still challenging in connectomics research.
1 code implementation • 19 Feb 2021 • Kanggeun Lee, Won-Ki Jeong
With the advent of advances in self-supervised learning, paired clean-noisy data are no longer required in deep learning-based image denoising.
no code implementations • 7 Dec 2020 • Kanggeun Lee, Won-Ki Jeong
In this paper, we propose a dilated convolutional network that satisfies an invariant property, allowing efficient kernel-based training without random masking.
2 code implementations • 23 Jun 2020 • Hyeonsoo Lee, Won-Ki Jeong
Segmentation is a fundamental process in microscopic cell image analysis.
no code implementations • 14 May 2020 • Tuan Tran Anh, Khoa Nguyen-Tuan, Tran Minh Quan, Won-Ki Jeong
To exploit the advantages of conventional single-object-per-step segmentation methods without impairing the scalability, we propose a novel iterative deep reinforcement learning agent that learns how to differentiate multiple objects in parallel.
1 code implementation • 3 Sep 2017 • Tran Minh Quan, Thanh Nguyen-Duc, Won-Ki Jeong
In this paper, we propose a novel deep learning-based generative adversarial model, RefineGAN, for fast and accurate CS-MRI reconstruction.
no code implementations • 25 Jul 2017 • Inwan Yoo, David G. C. Hildebrand, Willie F. Tobin, Wei-Chung Allen Lee, Won-Ki Jeong
The alignment of serial-section electron microscopy (ssEM) images is critical for efforts in neuroscience that seek to reconstruct neuronal circuits.
6 code implementations • 16 Dec 2016 • Tran Minh Quan, David G. C. Hildebrand, Won-Ki Jeong
Electron microscopic connectomics is an ambitious research direction with the goal of studying comprehensive brain connectivity maps by using high-throughput, nano-scale microscopy.