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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]
Project 2025 calls for taking that power away. The result would be a freer hand for drugmakers to set prices — and, almost surely, higher drug costs for seniors and people with disabilities on ...
Drafted by former advisers to Donald Trump’s administration, Project 2025 calls for various actions impacting civil rights, education, immigration, criminal […]
On immigration, Project 2025 calls for Immigration and Customs Enforcement to implement "expedited removal" of immigrants who lack legal status – a process normally only used at the border ...
Since its inception in 2013, ICLR has employed an open peer review process to referee paper submissions (based on models proposed by Yann LeCun [2]). In 2019, there were 1591 paper submissions, of which 500 accepted with poster presentations (31%) and 24 with oral presentations (1.5%). [ 3 ]
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]