all AI news
Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic Segmentation. (arXiv:2205.09722v1 [cs.CV])
cs.CV updates on arXiv.org arxiv.org
With the COVID-19 global pandemic, computer-assisted diagnoses of medical
images have gained much attention, and robust methods of Semantic Segmentation
of Computed Tomography (CT) became highly desirable. Semantic Segmentation of
CT is one of many research fields of automatic detection of COVID-19 and has
been widely explored since the COVID-19 outbreak. In this work, we propose an
extensive analysis of how different data augmentation techniques improve the
training of encoder-decoder neural networks on this problem. Twenty different
data augmentation techniques …
arxiv augmentation covid covid-19 cv data evaluation light segmentation semantic