Web: http://arxiv.org/abs/2209.06411

Sept. 15, 2022, 1:13 a.m. | Xuanyu Tian, Qing Wu, Hongjiang Wei, Yuyao Zhang

cs.CV updates on arXiv.org arxiv.org

Fluorescence microscopy is a key driver to promote discoveries of biomedical
research. However, with the limitation of microscope hardware and
characteristics of the observed samples, the fluorescence microscopy images are
susceptible to noise. Recently, a few self-supervised deep learning (DL)
denoising methods have been proposed. However, the training efficiency and
denoising performance of existing methods are relatively low in real scene
noise removal. To address this issue, this paper proposed self-supervised image
denoising method Noise2SR (N2SR) to train a simple …

arxiv image

More from arxiv.org / cs.CV updates on arXiv.org

Research Scientists

@ ODU Research Foundation | Norfolk, Virginia

Embedded Systems Engineer (Robotics)

@ Neo Cybernetica | Bedford, New Hampshire

2023 Luis J. Alvarez and Admiral Grace M. Hopper Postdoc Fellowship in Computing Sciences

@ Lawrence Berkeley National Lab | San Francisco, CA

Senior Manager Data Scientist

@ NAV | Remote, US

Senior AI Research Scientist

@ Earth Species Project | Remote anywhere

Research Fellow- Center for Security and Emerging Technology (Multiple Opportunities)

@ University of California Davis | Washington, DC

Staff Fellow - Data Scientist

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Staff Fellow - Senior Data Engineer

@ U.S. FDA/Center for Devices and Radiological Health | Silver Spring, Maryland

Data Scientist (Analytics) - Singapore

@ Momos | Singapore, Central, Singapore

Machine Learning Scientist, Drug Discovery

@ Flagship Pioneering, Inc. | Cambridge, MA

Applied Scientist - Computer Vision

@ Flawless | Los Angeles, California, United States

Sr. Data Engineer, Customer Service

@ Wayfair Inc. | Boston, MA