July 21, 2022, 1:12 a.m. | Omar Boudraa

cs.CV updates on arXiv.org arxiv.org

3D image segmentation is a recent and crucial step in many medical analysis
and recognition schemes. In fact, it represents a relevant research subject and
a fundamental challenge due to its importance and influence. This paper
provides a multi-phase Deep Learning-based system that hybridizes various
efficient methods in order to get the best 3D segmentation output. First, to
reduce the amount of data and accelerate the processing time, the application
of Decimate compression technique is suggested and justified. We then …

3d arxiv deep learning dental images learning segmentation

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Risk Management - Machine Learning and Model Delivery Services, Product Associate - Senior Associate-

@ JPMorgan Chase & Co. | Wilmington, DE, United States

Senior ML Engineer (Speech/ASR)

@ ObserveAI | Bengaluru