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Research in Computational Molecular Biology (RECOMB) is an annual academic conference on the subjects of bioinformatics and computational biology.The conference has been held every year since 1997 and is widely considered as one of two best international conferences in computational biology publishing rigorously peer-reviewed papers, alongside the ISMB conference.
Medical Image Computing (the "MIC" in MICCAI) is the field of study involving the application of image processing and computer vision to medical imaging.The goals of medical image computing tasks are diverse, but some common examples are computer-aided diagnosis, image segmentation of anatomical structures and/or abnormalities, and the registration or "alignment" of medical images acquired ...
The Vera C. Rubin Observatory is expected to begin science operations in late 2025. [45] [46] Science-related budgets US: Various details about planned science-related spending for 2025 have been described with some information on the planned research subjects or areas. [47] [48]
The highest monthly rate during Biden’s presidency was 9.1% in June 2022, ... Project 2025 calls for abortion monitor to track pregnancies, miscarriages ... according to a 2023 National Bureau ...
The Heritage Foundation launched the project in 2022 and published the policy collection in April 2023. ... Although retirement isn’t a primary focus for Project 2025, the plan calls for ...
The meeting is announced by way of a Call For Papers (CFP) or a Call For Abstracts, which is sent to prospective presenters and explains how to submit their abstracts or papers. It describes the broad theme and lists the meeting's topics and formalities such as what kind of abstract (summary) or paper has to be submitted, to whom, and by what ...
(Reuters) -U.S. President-elect Donald Trump has chosen Russ Vought, a key architect of "Project 2025," the controversial conservative plan to overhaul the government, to be director of the U.S ...
U-Net was created by Olaf Ronneberger, Philipp Fischer, Thomas Brox in 2015 and reported in the paper "U-Net: Convolutional Networks for Biomedical Image Segmentation". [1] It is an improvement and development of FCN: Evan Shelhamer, Jonathan Long, Trevor Darrell (2014). "Fully convolutional networks for semantic segmentation". [2]