{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/instant-image-denoising-plugin-for-imagej","title":"Instant Image Denoising Plugin for ImageJ using Convolutional Neural Networks","arxiv_id":"2006.13801","date":"2020-06-23","proceeding":null,"authors":["Varun Mannam","Yide Zhang","Yinhao Zhu","Scott Howard"],"abstract":"We present a new convolutional neural network (CNN) based ImageJ plugin for fluorescence microscopy image denoising with an average improvement of 7.5 dB in peak signal-to-noise ratio (PSNR) and denoising instantly within 80 msec.","url_abs":"http://arxiv.org/abs/2006.13801v1","url_pdf":"http://arxiv.org/pdf/2006.13801v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"instant-image-denoising-plugin-for-imagej","repo_url":"https://github.com/varunmannam/Image_denoising","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/intensity-image-denoising-on-fmd","task":"intensity image denoising","dataset":"FMD","model":"Noise2Noise and DnCNN","rank_in_archive_order":1,"of":1,"metrics":{"PSNR":"7.5dB improvement"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}