comparemela.com

Latest Breaking News On - சர்வதேச மாநாடு ஆன் இயந்திரம் - Page 1 : comparemela.com

Frontiers | Brain Differences Between Men and Women: Evidence From Deep Learning

2Department of Neurology, Xiangya Hospital, Central South University, Changsha, China 3Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States Do men and women have different brains? Previous neuroimage studies sought to answer this question based on morphological difference between specific brain regions, reporting unfortunately conflicting results. In the present study, we aim to use a deep learning technique to address this challenge based on a large open-access, diffusion MRI database recorded from 1,065 young healthy subjects, including 490 men and 575 women healthy subjects. Different from commonly used 2D Convolutional Neural Network (CNN), we proposed a 3D CNN method with a newly designed structure including three hidden layers in cascade with a linear layer and a terminal Softmax layer. The proposed 3D CNN was applied to the maps of factional anisotropy (FA) in the whole-brain as well as s

PhD student awarded IBM PhD Fellowship | WSU Insider | Washington State University

April 29, 2021 Syrine Belakaria Washington State University computer science doctoral candidate Syrine Belakaria is one of 16 students selected from around the world to receive the 2021 IBM Research PhD Fellowship. The highly competitive fellowship recognizes and supports exceptional PhD students who are working on promising and disruptive technologies, according to the IBM website. The two-year fellowship provides funding as well as mentorship with an IBM researcher in which students collaborate on a research or technology project. “As a PhD student, it is exciting to know that the research I am working on has potential for scientific impact as recognized by the external scientific community, and in this case, the IBM research institution,” Belakaria said. “This motivates me to continue with confidence in my research work.”

New Algorithm Could Reduce Complexity Of Big Data

New Algorithm Could Reduce Complexity Of Big Data Whenever a scientific experiment is conducted, the results are turned into numbers, often producing huge datasets. In order to reduce the size of the data, computer programmers use algorithms that can find and extract the principal features that represent the most salient statistical properties. But many such algorithms cannot be applied directly to these large volumes of data. Reza Oftadeh, doctoral student in the Department of Computer Science and Engineering at Texas A&M University, advised by Dylan Shell, faculty in the department, developed an algorithm applicable to large datasets that can directly order features from most salient to least.

© 2024 Vimarsana

vimarsana © 2020. All Rights Reserved.